Overview

Dataset statistics

Number of variables96
Number of observations73125
Missing cells5801798
Missing cells (%)82.6%
Duplicate rows983
Duplicate rows (%)1.3%
Total size in memory53.6 MiB
Average record size in memory768.0 B

Variable types

Categorical14
Text1
DateTime1
Numeric64
Unsupported16

Alerts

latitude has constant value "-26.2041"Constant
city has constant value "Johannesburg"Constant
Dataset has 983 (1.3%) duplicate rowsDuplicates
longitude is highly imbalanced (58.8%)Imbalance
sex is highly imbalanced (51.0%)Imbalance
race is highly imbalanced (64.3%)Imbalance
hiv_positive is highly imbalanced (71.9%)Imbalance
on_art is highly imbalanced (56.2%)Imbalance
heat_wave_day is highly imbalanced (83.9%)Imbalance
heat_stress_category is highly imbalanced (52.1%)Imbalance
visit_date has 23540 (32.2%) missing valuesMissing
year has 72237 (98.8%) missing valuesMissing
month has 72237 (98.8%) missing valuesMissing
season has 72237 (98.8%) missing valuesMissing
age_years has 23025 (31.5%) missing valuesMissing
sex has 18421 (25.2%) missing valuesMissing
race has 47197 (64.5%) missing valuesMissing
hiv_status has 2235 (3.1%) missing valuesMissing
hiv_positive has 17257 (23.6%) missing valuesMissing
on_art has 20091 (27.5%) missing valuesMissing
virally_suppressed has 73125 (100.0%) missing valuesMissing
cd4_count has 54285 (74.2%) missing valuesMissing
viral_load has 47507 (65.0%) missing valuesMissing
viral_load_undetectable has 46114 (63.1%) missing valuesMissing
log10_viral_load has 54490 (74.5%) missing valuesMissing
viral_load_wrhi003_category has 73125 (100.0%) missing valuesMissing
hemoglobin has 53329 (72.9%) missing valuesMissing
hematocrit has 55611 (76.0%) missing valuesMissing
rbc_count has 73125 (100.0%) missing valuesMissing
wbc_count has 73125 (100.0%) missing valuesMissing
platelet_count has 73125 (100.0%) missing valuesMissing
mcv has 63684 (87.1%) missing valuesMissing
mch has 64086 (87.6%) missing valuesMissing
mchc has 64086 (87.6%) missing valuesMissing
rdw has 64088 (87.6%) missing valuesMissing
neutrophils_pct has 73125 (100.0%) missing valuesMissing
lymphocytes_pct has 73125 (100.0%) missing valuesMissing
monocytes_pct has 73125 (100.0%) missing valuesMissing
eosinophils_pct has 73125 (100.0%) missing valuesMissing
basophils_pct has 73125 (100.0%) missing valuesMissing
fasting_glucose has 65898 (90.1%) missing valuesMissing
log10_fasting_glucose has 73125 (100.0%) missing valuesMissing
total_cholesterol has 65615 (89.7%) missing valuesMissing
hdl_cholesterol has 65617 (89.7%) missing valuesMissing
ldl_cholesterol has 65641 (89.8%) missing valuesMissing
triglycerides has 66534 (91.0%) missing valuesMissing
creatinine has 65195 (89.2%) missing valuesMissing
creatinine_clearance has 70598 (96.5%) missing valuesMissing
bun has 73125 (100.0%) missing valuesMissing
alt has 62768 (85.8%) missing valuesMissing
ast has 62769 (85.8%) missing valuesMissing
alp has 73125 (100.0%) missing valuesMissing
total_bilirubin has 64078 (87.6%) missing valuesMissing
albumin has 64067 (87.6%) missing valuesMissing
total_protein has 73125 (100.0%) missing valuesMissing
sodium has 64432 (88.1%) missing valuesMissing
potassium has 65017 (88.9%) missing valuesMissing
calcium has 73125 (100.0%) missing valuesMissing
systolic_bp has 34005 (46.5%) missing valuesMissing
diastolic_bp has 34004 (46.5%) missing valuesMissing
heart_rate has 34517 (47.2%) missing valuesMissing
temperature has 73125 (100.0%) missing valuesMissing
respiratory_rate has 48313 (66.1%) missing valuesMissing
oxygen_saturation has 57067 (78.0%) missing valuesMissing
height_m has 72586 (99.3%) missing valuesMissing
weight_kg has 53787 (73.6%) missing valuesMissing
bmi has 64455 (88.1%) missing valuesMissing
waist_circumference has 71558 (97.9%) missing valuesMissing
temp_mean_c has 72237 (98.8%) missing valuesMissing
temp_max_c has 72237 (98.8%) missing valuesMissing
temp_min_c has 72237 (98.8%) missing valuesMissing
temp_range_c has 72237 (98.8%) missing valuesMissing
temp_lag1d has 72237 (98.8%) missing valuesMissing
temp_lag3d has 72237 (98.8%) missing valuesMissing
temp_lag7d has 72237 (98.8%) missing valuesMissing
temp_lag14d has 72237 (98.8%) missing valuesMissing
temp_lag21d has 72237 (98.8%) missing valuesMissing
temp_lag30d has 72237 (98.8%) missing valuesMissing
temp_variability_7d has 72237 (98.8%) missing valuesMissing
temp_variability_30d has 72237 (98.8%) missing valuesMissing
apparent_temp has 72237 (98.8%) missing valuesMissing
temp_anomaly has 72237 (98.8%) missing valuesMissing
heat_wave_day has 72237 (98.8%) missing valuesMissing
heat_stress_category has 72237 (98.8%) missing valuesMissing
fasting_insulin has 71412 (97.7%) missing valuesMissing
hba1c has 72140 (98.7%) missing valuesMissing
hs_crp has 72170 (98.7%) missing valuesMissing
who_glycemic_status has 72144 (98.7%) missing valuesMissing
hip_circumference has 71558 (97.9%) missing valuesMissing
waist_hip_ratio has 71558 (97.9%) missing valuesMissing
total_fat_mass has 71397 (97.6%) missing valuesMissing
total_lean_mass has 71397 (97.6%) missing valuesMissing
body_fat_percent has 71397 (97.6%) missing valuesMissing
android_fat_percent has 72171 (98.7%) missing valuesMissing
fat_mass_index has 72173 (98.7%) missing valuesMissing
asmi has 72173 (98.7%) missing valuesMissing
grip_strength has 71603 (97.9%) missing valuesMissing
epworth_sleepiness_score has 72126 (98.6%) missing valuesMissing
ses_score has 71504 (97.8%) missing valuesMissing
asset_index has 72113 (98.6%) missing valuesMissing
vitamin_d has 72692 (99.4%) missing valuesMissing
waist_hip_ratio is highly skewed (γ1 = 22.78221434)Skewed
virally_suppressed is an unsupported type, check if it needs cleaning or further analysisUnsupported
viral_load_wrhi003_category is an unsupported type, check if it needs cleaning or further analysisUnsupported
rbc_count is an unsupported type, check if it needs cleaning or further analysisUnsupported
wbc_count is an unsupported type, check if it needs cleaning or further analysisUnsupported
platelet_count is an unsupported type, check if it needs cleaning or further analysisUnsupported
neutrophils_pct is an unsupported type, check if it needs cleaning or further analysisUnsupported
lymphocytes_pct is an unsupported type, check if it needs cleaning or further analysisUnsupported
monocytes_pct is an unsupported type, check if it needs cleaning or further analysisUnsupported
eosinophils_pct is an unsupported type, check if it needs cleaning or further analysisUnsupported
basophils_pct is an unsupported type, check if it needs cleaning or further analysisUnsupported
log10_fasting_glucose is an unsupported type, check if it needs cleaning or further analysisUnsupported
bun is an unsupported type, check if it needs cleaning or further analysisUnsupported
alp is an unsupported type, check if it needs cleaning or further analysisUnsupported
total_protein is an unsupported type, check if it needs cleaning or further analysisUnsupported
calcium is an unsupported type, check if it needs cleaning or further analysisUnsupported
temperature is an unsupported type, check if it needs cleaning or further analysisUnsupported
viral_load has 1291 (1.8%) zerosZeros
log10_viral_load has 1210 (1.7%) zerosZeros

Reproduction

Analysis started2025-12-02 16:32:05.881557
Analysis finished2025-12-02 16:32:07.203238
Duration1.32 second
Software versionydata-profiling vv4.18.0
Download configurationconfig.json

Variables

study_source
Categorical

Distinct17
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size571.4 KiB
JHB_WRHI_001
21015 
JHB_VIDA_007
15581 
JHB_Aurum_009
12575 
JHB_Ezin_002
11059 
JHB_ACTG_019
2594 
Other values (12)
10301 

Length

Max length14
Median length12
Mean length12.244732
Min length12

Characters and Unicode

Total characters895396
Distinct characters35
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowJHB_ACTG_015
2nd rowJHB_ACTG_015
3rd rowJHB_ACTG_015
4th rowJHB_ACTG_015
5th rowJHB_ACTG_015

Common Values

ValueCountFrequency (%)
JHB_WRHI_00121015
28.7%
JHB_VIDA_00715581
21.3%
JHB_Aurum_00912575
17.2%
JHB_Ezin_00211059
15.1%
JHB_ACTG_0192594
 
3.5%
JHB_ACTG_0152364
 
3.2%
JHB_WRHI_0032235
 
3.1%
JHB_SCHARP_0061359
 
1.9%
JHB_DPHRU_0531013
 
1.4%
JHB_DPHRU_013784
 
1.1%
Other values (7)2546
 
3.5%

Length

2025-12-02T18:32:07.304393image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
jhb_wrhi_00121015
28.7%
jhb_vida_00715581
21.3%
jhb_aurum_00912575
17.2%
jhb_ezin_00211059
15.1%
jhb_actg_0192594
 
3.5%
jhb_actg_0152364
 
3.2%
jhb_wrhi_0032235
 
3.1%
jhb_scharp_0061359
 
1.9%
jhb_dphru_0531013
 
1.4%
jhb_dphru_013784
 
1.1%
Other values (7)2546
 
3.5%

Most occurring characters

ValueCountFrequency (%)
_146250
16.3%
0137902
15.4%
H99934
11.2%
J73125
 
8.2%
B73125
 
8.2%
I39870
 
4.5%
A36530
 
4.1%
127861
 
3.1%
R26809
 
3.0%
u25150
 
2.8%
Other values (25)208840
23.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter446294
49.8%
Decimal Number219375
24.5%
Connector Punctuation146250
 
16.3%
Lowercase Letter83477
 
9.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
H99934
22.4%
J73125
16.4%
B73125
16.4%
I39870
 
8.9%
A36530
 
8.2%
R26809
 
6.0%
W23250
 
5.2%
D17928
 
4.0%
V16131
 
3.6%
E11548
 
2.6%
Other values (8)28044
 
6.3%
Decimal Number
ValueCountFrequency (%)
0137902
62.9%
127861
 
12.7%
715601
 
7.1%
915169
 
6.9%
211626
 
5.3%
34032
 
1.8%
53866
 
1.8%
62125
 
1.0%
8790
 
0.4%
4403
 
0.2%
Lowercase Letter
ValueCountFrequency (%)
u25150
30.1%
r12575
15.1%
m12575
15.1%
i11059
13.2%
n11059
13.2%
z11059
13.2%
Connector Punctuation
ValueCountFrequency (%)
_146250
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin529771
59.2%
Common365625
40.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
H99934
18.9%
J73125
13.8%
B73125
13.8%
I39870
 
7.5%
A36530
 
6.9%
R26809
 
5.1%
u25150
 
4.7%
W23250
 
4.4%
D17928
 
3.4%
V16131
 
3.0%
Other values (14)97919
18.5%
Common
ValueCountFrequency (%)
_146250
40.0%
0137902
37.7%
127861
 
7.6%
715601
 
4.3%
915169
 
4.1%
211626
 
3.2%
34032
 
1.1%
53866
 
1.1%
62125
 
0.6%
8790
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII895396
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
_146250
16.3%
0137902
15.4%
H99934
11.2%
J73125
 
8.2%
B73125
 
8.2%
I39870
 
4.5%
A36530
 
4.1%
127861
 
3.1%
R26809
 
3.0%
u25150
 
2.8%
Other values (25)208840
23.3%
Distinct12804
Distinct (%)17.5%
Missing0
Missing (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:07.392578image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length22
Median length5
Mean length8.4818598
Min length1

Characters and Unicode

Total characters620236
Distinct characters39
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4781 ?
Unique (%)6.5%

Sample

1st row1110060
2nd row1110060
3rd row1110060
4th row1110060
5th row1110060
ValueCountFrequency (%)
wbs784
 
1.1%
3002780
 
0.1%
3015248
 
0.1%
1029444
 
0.1%
2037239
 
0.1%
2046238
 
0.1%
3005238
 
0.1%
111004837
 
0.1%
111003936
 
< 0.1%
20636
 
< 0.1%
Other values (12638)72729
98.4%
2025-12-02T18:32:07.530409image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0113623
18.3%
193363
15.1%
-73934
11.9%
941342
 
6.7%
239266
 
6.3%
532748
 
5.3%
730920
 
5.0%
328610
 
4.6%
422265
 
3.6%
619586
 
3.2%
Other values (29)124579
20.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number437923
70.6%
Uppercase Letter106707
 
17.2%
Dash Punctuation73934
 
11.9%
Connector Punctuation888
 
0.1%
Space Separator784
 
0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A16074
15.1%
U14703
 
13.8%
R14698
 
13.8%
S3952
 
3.7%
E3929
 
3.7%
B3601
 
3.4%
G3153
 
3.0%
K3132
 
2.9%
H3124
 
2.9%
T3116
 
2.9%
Other values (16)37225
34.9%
Decimal Number
ValueCountFrequency (%)
0113623
25.9%
193363
21.3%
941342
 
9.4%
239266
 
9.0%
532748
 
7.5%
730920
 
7.1%
328610
 
6.5%
422265
 
5.1%
619586
 
4.5%
816200
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
-73934
100.0%
Connector Punctuation
ValueCountFrequency (%)
_888
100.0%
Space Separator
ValueCountFrequency (%)
784
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common513529
82.8%
Latin106707
 
17.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
A16074
15.1%
U14703
 
13.8%
R14698
 
13.8%
S3952
 
3.7%
E3929
 
3.7%
B3601
 
3.4%
G3153
 
3.0%
K3132
 
2.9%
H3124
 
2.9%
T3116
 
2.9%
Other values (16)37225
34.9%
Common
ValueCountFrequency (%)
0113623
22.1%
193363
18.2%
-73934
14.4%
941342
 
8.1%
239266
 
7.6%
532748
 
6.4%
730920
 
6.0%
328610
 
5.6%
422265
 
4.3%
619586
 
3.8%
Other values (3)17872
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII620236
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0113623
18.3%
193363
15.1%
-73934
11.9%
941342
 
6.7%
239266
 
6.3%
532748
 
5.3%
730920
 
5.0%
328610
 
4.6%
422265
 
3.6%
619586
 
3.2%
Other values (29)124579
20.1%

visit_date
Date

Missing 

Distinct3373
Distinct (%)6.8%
Missing23540
Missing (%)32.2%
Memory size571.4 KiB
Minimum2003-10-20 00:00:00
Maximum2021-12-09 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2025-12-02T18:32:07.585495image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2025-12-02T18:32:07.630500image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

year
Real number (ℝ)

Missing 

Distinct8
Distinct (%)0.9%
Missing72237
Missing (%)98.8%
Infinite0
Infinite (%)0.0%
Mean2016.2646
Minimum2003
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:07.667888image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum2003
5-th percentile2006
Q12011
median2020
Q32020
95-th percentile2021
Maximum2021
Range18
Interquartile range (IQR)9

Descriptive statistics

Standard deviation5.3887027
Coefficient of variation (CV)0.0026726168
Kurtosis-0.87532698
Mean2016.2646
Median Absolute Deviation (MAD)1
Skewness-0.79511657
Sum1790443
Variance29.038117
MonotonicityNot monotonic
2025-12-02T18:32:07.704068image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
2020397
 
0.5%
2011153
 
0.2%
2021153
 
0.2%
201287
 
0.1%
200658
 
0.1%
200720
 
< 0.1%
200415
 
< 0.1%
20035
 
< 0.1%
(Missing)72237
98.8%
ValueCountFrequency (%)
20035
 
< 0.1%
200415
 
< 0.1%
200658
 
0.1%
200720
 
< 0.1%
2011153
 
0.2%
201287
 
0.1%
2020397
0.5%
2021153
 
0.2%
ValueCountFrequency (%)
2021153
 
0.2%
2020397
0.5%
201287
 
0.1%
2011153
 
0.2%
200720
 
< 0.1%
200658
 
0.1%
200415
 
< 0.1%
20035
 
< 0.1%

month
Real number (ℝ)

Missing 

Distinct12
Distinct (%)1.4%
Missing72237
Missing (%)98.8%
Infinite0
Infinite (%)0.0%
Mean5.7083333
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:07.743257image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q14
median5
Q37
95-th percentile10
Maximum12
Range11
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.2682203
Coefficient of variation (CV)0.39735246
Kurtosis0.33389557
Mean5.7083333
Median Absolute Deviation (MAD)1
Skewness0.52055179
Sum5069
Variance5.1448234
MonotonicityNot monotonic
2025-12-02T18:32:07.778075image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
5253
 
0.3%
6158
 
0.2%
4127
 
0.2%
789
 
0.1%
849
 
0.1%
1048
 
0.1%
338
 
0.1%
237
 
0.1%
1131
 
< 0.1%
127
 
< 0.1%
Other values (2)31
 
< 0.1%
(Missing)72237
98.8%
ValueCountFrequency (%)
127
 
< 0.1%
237
 
0.1%
338
 
0.1%
4127
0.2%
5253
0.3%
6158
0.2%
789
 
0.1%
849
 
0.1%
925
 
< 0.1%
1048
 
0.1%
ValueCountFrequency (%)
126
 
< 0.1%
1131
 
< 0.1%
1048
 
0.1%
925
 
< 0.1%
849
 
0.1%
789
 
0.1%
6158
0.2%
5253
0.3%
4127
0.2%
338
 
0.1%

season
Categorical

Missing 

Distinct4
Distinct (%)0.5%
Missing72237
Missing (%)98.8%
Memory size571.4 KiB
Autumn
418 
Winter
296 
Spring
104 
Summer
70 

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters5328
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSpring
2nd rowWinter
3rd rowSummer
4th rowSummer
5th rowSummer

Common Values

ValueCountFrequency (%)
Autumn418
 
0.6%
Winter296
 
0.4%
Spring104
 
0.1%
Summer70
 
0.1%
(Missing)72237
98.8%

Length

2025-12-02T18:32:07.817732image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-12-02T18:32:07.856616image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
autumn418
47.1%
winter296
33.3%
spring104
 
11.7%
summer70
 
7.9%

Most occurring characters

ValueCountFrequency (%)
u906
17.0%
n818
15.4%
t714
13.4%
m558
10.5%
r470
8.8%
A418
7.8%
i400
7.5%
e366
6.9%
W296
 
5.6%
S174
 
3.3%
Other values (2)208
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4440
83.3%
Uppercase Letter888
 
16.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u906
20.4%
n818
18.4%
t714
16.1%
m558
12.6%
r470
10.6%
i400
9.0%
e366
8.2%
p104
 
2.3%
g104
 
2.3%
Uppercase Letter
ValueCountFrequency (%)
A418
47.1%
W296
33.3%
S174
19.6%

Most occurring scripts

ValueCountFrequency (%)
Latin5328
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
u906
17.0%
n818
15.4%
t714
13.4%
m558
10.5%
r470
8.8%
A418
7.8%
i400
7.5%
e366
6.9%
W296
 
5.6%
S174
 
3.3%
Other values (2)208
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII5328
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
u906
17.0%
n818
15.4%
t714
13.4%
m558
10.5%
r470
8.8%
A418
7.8%
i400
7.5%
e366
6.9%
W296
 
5.6%
S174
 
3.3%
Other values (2)208
 
3.9%

latitude
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size571.4 KiB
-26.2041
73125 

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters585000
Distinct characters7
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row-26.2041
2nd row-26.2041
3rd row-26.2041
4th row-26.2041
5th row-26.2041

Common Values

ValueCountFrequency (%)
-26.204173125
100.0%

Length

2025-12-02T18:32:07.904331image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-12-02T18:32:07.941519image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
26.204173125
100.0%

Most occurring characters

ValueCountFrequency (%)
2146250
25.0%
-73125
12.5%
673125
12.5%
.73125
12.5%
073125
12.5%
473125
12.5%
173125
12.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number438750
75.0%
Dash Punctuation73125
 
12.5%
Other Punctuation73125
 
12.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2146250
33.3%
673125
16.7%
073125
16.7%
473125
16.7%
173125
16.7%
Dash Punctuation
ValueCountFrequency (%)
-73125
100.0%
Other Punctuation
ValueCountFrequency (%)
.73125
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common585000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2146250
25.0%
-73125
12.5%
673125
12.5%
.73125
12.5%
073125
12.5%
473125
12.5%
173125
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII585000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2146250
25.0%
-73125
12.5%
673125
12.5%
.73125
12.5%
073125
12.5%
473125
12.5%
173125
12.5%

longitude
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size571.4 KiB
28.0473
67063 
27.9394
 
6062

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters511875
Distinct characters8
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row27.9394
2nd row27.9394
3rd row27.9394
4th row27.9394
5th row27.9394

Common Values

ValueCountFrequency (%)
28.047367063
91.7%
27.93946062
 
8.3%

Length

2025-12-02T18:32:07.978577image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-12-02T18:32:08.014963image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
28.047367063
91.7%
27.93946062
 
8.3%

Most occurring characters

ValueCountFrequency (%)
273125
14.3%
.73125
14.3%
473125
14.3%
773125
14.3%
373125
14.3%
867063
13.1%
067063
13.1%
912124
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number438750
85.7%
Other Punctuation73125
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
273125
16.7%
473125
16.7%
773125
16.7%
373125
16.7%
867063
15.3%
067063
15.3%
912124
 
2.8%
Other Punctuation
ValueCountFrequency (%)
.73125
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common511875
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
273125
14.3%
.73125
14.3%
473125
14.3%
773125
14.3%
373125
14.3%
867063
13.1%
067063
13.1%
912124
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII511875
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
273125
14.3%
.73125
14.3%
473125
14.3%
773125
14.3%
373125
14.3%
867063
13.1%
067063
13.1%
912124
 
2.4%

city
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size571.4 KiB
Johannesburg
73125 

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters877500
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowJohannesburg
2nd rowJohannesburg
3rd rowJohannesburg
4th rowJohannesburg
5th rowJohannesburg

Common Values

ValueCountFrequency (%)
Johannesburg73125
100.0%

Length

2025-12-02T18:32:08.051946image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-12-02T18:32:08.085466image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
johannesburg73125
100.0%

Most occurring characters

ValueCountFrequency (%)
n146250
16.7%
J73125
8.3%
o73125
8.3%
h73125
8.3%
a73125
8.3%
e73125
8.3%
s73125
8.3%
b73125
8.3%
u73125
8.3%
r73125
8.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter804375
91.7%
Uppercase Letter73125
 
8.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n146250
18.2%
o73125
9.1%
h73125
9.1%
a73125
9.1%
e73125
9.1%
s73125
9.1%
b73125
9.1%
u73125
9.1%
r73125
9.1%
g73125
9.1%
Uppercase Letter
ValueCountFrequency (%)
J73125
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin877500
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n146250
16.7%
J73125
8.3%
o73125
8.3%
h73125
8.3%
a73125
8.3%
e73125
8.3%
s73125
8.3%
b73125
8.3%
u73125
8.3%
r73125
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII877500
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n146250
16.7%
J73125
8.3%
o73125
8.3%
h73125
8.3%
a73125
8.3%
e73125
8.3%
s73125
8.3%
b73125
8.3%
u73125
8.3%
r73125
8.3%

age_years
Real number (ℝ)

Missing 

Distinct741
Distinct (%)1.5%
Missing23025
Missing (%)31.5%
Infinite0
Infinite (%)0.0%
Mean35.102974
Minimum13
Maximum76
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:08.121741image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum13
5-th percentile21
Q128
median34
Q341
95-th percentile53
Maximum76
Range63
Interquartile range (IQR)13

Descriptive statistics

Standard deviation9.5751026
Coefficient of variation (CV)0.27277183
Kurtosis-0.021029012
Mean35.102974
Median Absolute Deviation (MAD)7
Skewness0.52637056
Sum1758659
Variance91.682591
MonotonicityNot monotonic
2025-12-02T18:32:08.168441image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
332131
 
2.9%
352112
 
2.9%
342085
 
2.9%
302052
 
2.8%
281961
 
2.7%
311944
 
2.7%
261928
 
2.6%
321844
 
2.5%
401775
 
2.4%
371766
 
2.4%
Other values (731)30502
41.7%
(Missing)23025
31.5%
ValueCountFrequency (%)
133
 
< 0.1%
147
 
< 0.1%
1518
 
< 0.1%
1632
 
< 0.1%
1795
 
0.1%
18395
0.5%
18.11
 
< 0.1%
18.81
 
< 0.1%
19592
0.8%
19.31
 
< 0.1%
ValueCountFrequency (%)
765
 
< 0.1%
757
 
< 0.1%
745
 
< 0.1%
735
 
< 0.1%
7111
 
< 0.1%
6921
< 0.1%
6811
 
< 0.1%
6713
 
< 0.1%
6648
0.1%
6510
 
< 0.1%

sex
Categorical

Imbalance  Missing 

Distinct4
Distinct (%)< 0.1%
Missing18421
Missing (%)25.2%
Memory size571.4 KiB
Female
34885 
Male
19578 
Unknown
 
240
Not available
 
1

Length

Max length13
Median length6
Mean length5.2887357
Min length4

Characters and Unicode

Total characters289315
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowFemale
2nd rowFemale
3rd rowFemale
4th rowFemale
5th rowFemale

Common Values

ValueCountFrequency (%)
Female34885
47.7%
Male19578
26.8%
Unknown240
 
0.3%
Not available1
 
< 0.1%
(Missing)18421
25.2%

Length

2025-12-02T18:32:08.220525image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-12-02T18:32:08.254703image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
female34885
63.8%
male19578
35.8%
unknown240
 
0.4%
not1
 
< 0.1%
available1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
e89349
30.9%
a54466
18.8%
l54465
18.8%
F34885
 
12.1%
m34885
 
12.1%
M19578
 
6.8%
n720
 
0.2%
o241
 
0.1%
w240
 
0.1%
k240
 
0.1%
Other values (7)246
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter234610
81.1%
Uppercase Letter54704
 
18.9%
Space Separator1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e89349
38.1%
a54466
23.2%
l54465
23.2%
m34885
 
14.9%
n720
 
0.3%
o241
 
0.1%
w240
 
0.1%
k240
 
0.1%
t1
 
< 0.1%
v1
 
< 0.1%
Other values (2)2
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
F34885
63.8%
M19578
35.8%
U240
 
0.4%
N1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin289314
> 99.9%
Common1
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e89349
30.9%
a54466
18.8%
l54465
18.8%
F34885
 
12.1%
m34885
 
12.1%
M19578
 
6.8%
n720
 
0.2%
o241
 
0.1%
w240
 
0.1%
k240
 
0.1%
Other values (6)245
 
0.1%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII289315
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e89349
30.9%
a54466
18.8%
l54465
18.8%
F34885
 
12.1%
m34885
 
12.1%
M19578
 
6.8%
n720
 
0.2%
o241
 
0.1%
w240
 
0.1%
k240
 
0.1%
Other values (7)246
 
0.1%

race
Categorical

Imbalance  Missing 

Distinct7
Distinct (%)< 0.1%
Missing47197
Missing (%)64.5%
Memory size571.4 KiB
African Heritage
20870 
Black
2634 
Asian
 
1951
Caucasian
 
301
White
 
60
Other values (2)
 
112

Length

Max length16
Median length16
Mean length13.907282
Min length5

Characters and Unicode

Total characters360588
Distinct characters23
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAfrican Heritage
2nd rowAfrican Heritage
3rd rowAfrican Heritage
4th rowAsian
5th rowAfrican Heritage

Common Values

ValueCountFrequency (%)
African Heritage20870
28.5%
Black2634
 
3.6%
Asian1951
 
2.7%
Caucasian301
 
0.4%
White60
 
0.1%
Coloured58
 
0.1%
Other54
 
0.1%
(Missing)47197
64.5%

Length

2025-12-02T18:32:08.292985image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-12-02T18:32:08.338966image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
african20870
44.6%
heritage20870
44.6%
black2634
 
5.6%
asian1951
 
4.2%
caucasian301
 
0.6%
white60
 
0.1%
coloured58
 
0.1%
other54
 
0.1%

Most occurring characters

ValueCountFrequency (%)
a47228
13.1%
i44052
12.2%
e41912
11.6%
r41852
11.6%
c23805
6.6%
n23122
6.4%
A22821
6.3%
t20984
 
5.8%
f20870
 
5.8%
g20870
 
5.8%
Other values (13)53072
14.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter292920
81.2%
Uppercase Letter46798
 
13.0%
Space Separator20870
 
5.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a47228
16.1%
i44052
15.0%
e41912
14.3%
r41852
14.3%
c23805
8.1%
n23122
7.9%
t20984
7.2%
f20870
7.1%
g20870
7.1%
l2692
 
0.9%
Other values (6)5533
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
A22821
48.8%
H20870
44.6%
B2634
 
5.6%
C359
 
0.8%
W60
 
0.1%
O54
 
0.1%
Space Separator
ValueCountFrequency (%)
20870
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin339718
94.2%
Common20870
 
5.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a47228
13.9%
i44052
13.0%
e41912
12.3%
r41852
12.3%
c23805
7.0%
n23122
6.8%
A22821
6.7%
t20984
6.2%
f20870
6.1%
g20870
6.1%
Other values (12)32202
9.5%
Common
ValueCountFrequency (%)
20870
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII360588
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a47228
13.1%
i44052
12.2%
e41912
11.6%
r41852
11.6%
c23805
6.6%
n23122
6.4%
A22821
6.3%
t20984
 
5.8%
f20870
 
5.8%
g20870
 
5.8%
Other values (13)53072
14.7%

hiv_status
Categorical

Missing 

Distinct3
Distinct (%)< 0.1%
Missing2235
Missing (%)3.1%
Memory size571.4 KiB
Positive
53145 
Unknown
16386 
Negative
 
1359

Length

Max length8
Median length8
Mean length7.7688532
Min length7

Characters and Unicode

Total characters550734
Distinct characters14
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPositive
2nd rowPositive
3rd rowPositive
4th rowPositive
5th rowPositive

Common Values

ValueCountFrequency (%)
Positive53145
72.7%
Unknown16386
 
22.4%
Negative1359
 
1.9%
(Missing)2235
 
3.1%

Length

2025-12-02T18:32:08.382446image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-12-02T18:32:08.418792image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
positive53145
75.0%
unknown16386
 
23.1%
negative1359
 
1.9%

Most occurring characters

ValueCountFrequency (%)
i107649
19.5%
o69531
12.6%
e55863
10.1%
t54504
9.9%
v54504
9.9%
P53145
9.6%
s53145
9.6%
n49158
8.9%
U16386
 
3.0%
k16386
 
3.0%
Other values (4)20463
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter479844
87.1%
Uppercase Letter70890
 
12.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i107649
22.4%
o69531
14.5%
e55863
11.6%
t54504
11.4%
v54504
11.4%
s53145
11.1%
n49158
10.2%
k16386
 
3.4%
w16386
 
3.4%
g1359
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
P53145
75.0%
U16386
 
23.1%
N1359
 
1.9%

Most occurring scripts

ValueCountFrequency (%)
Latin550734
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i107649
19.5%
o69531
12.6%
e55863
10.1%
t54504
9.9%
v54504
9.9%
P53145
9.6%
s53145
9.6%
n49158
8.9%
U16386
 
3.0%
k16386
 
3.0%
Other values (4)20463
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII550734
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i107649
19.5%
o69531
12.6%
e55863
10.1%
t54504
9.9%
v54504
9.9%
P53145
9.6%
s53145
9.6%
n49158
8.9%
U16386
 
3.0%
k16386
 
3.0%
Other values (4)20463
 
3.7%

hiv_positive
Categorical

Imbalance  Missing 

Distinct2
Distinct (%)< 0.1%
Missing17257
Missing (%)23.6%
Memory size571.4 KiB
1.0
53145 
0.0
 
2723

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters167604
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.053145
72.7%
0.02723
 
3.7%
(Missing)17257
 
23.6%

Length

2025-12-02T18:32:08.458399image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-12-02T18:32:08.492376image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
1.053145
95.1%
0.02723
 
4.9%

Most occurring characters

ValueCountFrequency (%)
058591
35.0%
.55868
33.3%
153145
31.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number111736
66.7%
Other Punctuation55868
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
058591
52.4%
153145
47.6%
Other Punctuation
ValueCountFrequency (%)
.55868
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common167604
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
058591
35.0%
.55868
33.3%
153145
31.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII167604
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
058591
35.0%
.55868
33.3%
153145
31.7%

on_art
Categorical

Imbalance  Missing 

Distinct3
Distinct (%)< 0.1%
Missing20091
Missing (%)27.5%
Memory size571.4 KiB
1.0
43189 
0.0
9837 
8.0
 
8

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters159102
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.043189
59.1%
0.09837
 
13.5%
8.08
 
< 0.1%
(Missing)20091
27.5%

Length

2025-12-02T18:32:08.527241image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-12-02T18:32:08.561274image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
1.043189
81.4%
0.09837
 
18.5%
8.08
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
062871
39.5%
.53034
33.3%
143189
27.1%
88
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number106068
66.7%
Other Punctuation53034
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
062871
59.3%
143189
40.7%
88
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
.53034
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common159102
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
062871
39.5%
.53034
33.3%
143189
27.1%
88
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII159102
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
062871
39.5%
.53034
33.3%
143189
27.1%
88
 
< 0.1%

virally_suppressed
Unsupported

Missing  Rejected  Unsupported 

Missing73125
Missing (%)100.0%
Memory size571.4 KiB

cd4_count
Real number (ℝ)

Missing 

Distinct1153
Distinct (%)6.1%
Missing54285
Missing (%)74.2%
Infinite0
Infinite (%)0.0%
Mean536.75515
Minimum0.07
Maximum9999
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:08.602327image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.07
5-th percentile90
Q1226
median340
Q3485
95-th percentile834
Maximum9999
Range9998.93
Interquartile range (IQR)259

Descriptive statistics

Standard deviation1275.6569
Coefficient of variation (CV)2.3766086
Kurtosis49.574306
Mean536.75515
Median Absolute Deviation (MAD)127
Skewness7.0803243
Sum10112467
Variance1627300.5
MonotonicityNot monotonic
2025-12-02T18:32:08.649130image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9999325
 
0.4%
31563
 
0.1%
30056
 
0.1%
32352
 
0.1%
38151
 
0.1%
29250
 
0.1%
32950
 
0.1%
32150
 
0.1%
34850
 
0.1%
35050
 
0.1%
Other values (1143)18043
 
24.7%
(Missing)54285
74.2%
ValueCountFrequency (%)
0.071
 
< 0.1%
13
 
< 0.1%
25
< 0.1%
34
 
< 0.1%
43
 
< 0.1%
510
< 0.1%
67
< 0.1%
75
< 0.1%
89
< 0.1%
910
< 0.1%
ValueCountFrequency (%)
9999325
0.4%
99971
 
< 0.1%
99901
 
< 0.1%
50001
 
< 0.1%
27031
 
< 0.1%
26092
 
< 0.1%
20801
 
< 0.1%
19961
 
< 0.1%
19001
 
< 0.1%
17811
 
< 0.1%

viral_load
Real number (ℝ)

Missing  Zeros 

Distinct5061
Distinct (%)19.8%
Missing47507
Missing (%)65.0%
Infinite0
Infinite (%)0.0%
Mean1024570.9
Minimum0
Maximum99999999
Zeros1291
Zeros (%)1.8%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:08.695125image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q139
median82
Q3986
95-th percentile438001.5
Maximum99999999
Range99999999
Interquartile range (IQR)947

Descriptive statistics

Standard deviation7532920.1
Coefficient of variation (CV)7.3522679
Kurtosis90.767427
Mean1024570.9
Median Absolute Deviation (MAD)82
Skewness9.1388789
Sum2.6247459 × 1010
Variance5.6744886 × 1013
MonotonicityNot monotonic
2025-12-02T18:32:08.742078image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
397909
 
10.8%
4004425
 
6.1%
01291
 
1.8%
191235
 
1.7%
11210
 
1.7%
40252
 
0.3%
750000137
 
0.2%
4141
 
0.1%
4839
 
0.1%
4436
 
< 0.1%
Other values (5051)9043
 
12.4%
(Missing)47507
65.0%
ValueCountFrequency (%)
01291
1.8%
11210
1.7%
105
 
< 0.1%
191235
1.7%
208
 
< 0.1%
2112
 
< 0.1%
2225
 
< 0.1%
2319
 
< 0.1%
2416
 
< 0.1%
2510
 
< 0.1%
ValueCountFrequency (%)
999999994
 
< 0.1%
962990005
< 0.1%
9590000010
< 0.1%
958130005
< 0.1%
951410005
< 0.1%
940250005
< 0.1%
940000005
< 0.1%
924920005
< 0.1%
899910005
< 0.1%
855500005
< 0.1%

viral_load_undetectable
Categorical

Missing 

Distinct2
Distinct (%)< 0.1%
Missing46114
Missing (%)63.1%
Memory size571.4 KiB
1.0
16449 
0.0
10562 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters81033
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
1.016449
 
22.5%
0.010562
 
14.4%
(Missing)46114
63.1%

Length

2025-12-02T18:32:08.787773image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-12-02T18:32:08.821010image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
1.016449
60.9%
0.010562
39.1%

Most occurring characters

ValueCountFrequency (%)
037573
46.4%
.27011
33.3%
116449
20.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number54022
66.7%
Other Punctuation27011
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
037573
69.6%
116449
30.4%
Other Punctuation
ValueCountFrequency (%)
.27011
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common81033
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
037573
46.4%
.27011
33.3%
116449
20.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII81033
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
037573
46.4%
.27011
33.3%
116449
20.3%

log10_viral_load
Real number (ℝ)

Missing  Zeros 

Distinct4410
Distinct (%)23.7%
Missing54490
Missing (%)74.5%
Infinite0
Infinite (%)0.0%
Mean2.489943
Minimum0
Maximum8
Zeros1210
Zeros (%)1.7%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:08.860762image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.5910646
median1.5910646
Q33.4782777
95-th percentile5.7515601
Maximum8
Range8
Interquartile range (IQR)1.8872131

Descriptive statistics

Standard deviation1.7249255
Coefficient of variation (CV)0.69275702
Kurtosis0.77422242
Mean2.489943
Median Absolute Deviation (MAD)0.31231101
Skewness1.1693433
Sum46400.088
Variance2.9753679
MonotonicityNot monotonic
2025-12-02T18:32:08.908678image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.5910646077909
 
10.8%
1.2787536011235
 
1.7%
01210
 
1.7%
1.602059991252
 
0.3%
1.61278385741
 
0.1%
1.68124123739
 
0.1%
1.64345267636
 
< 0.1%
1.65321251435
 
< 0.1%
1.6232492934
 
< 0.1%
1.67209785834
 
< 0.1%
Other values (4400)7810
 
10.7%
(Missing)54490
74.5%
ValueCountFrequency (%)
01210
1.7%
15
 
< 0.1%
1.2787536011235
1.7%
1.3010299968
 
< 0.1%
1.32221929512
 
< 0.1%
1.34242268125
 
< 0.1%
1.36172783619
 
< 0.1%
1.38021124216
 
< 0.1%
1.39794000910
 
< 0.1%
1.41497334813
 
< 0.1%
ValueCountFrequency (%)
7.9999999964
 
< 0.1%
7.9836217775
< 0.1%
7.98181860710
< 0.1%
7.9814244395
< 0.1%
7.9783677125
< 0.1%
7.9732433425
< 0.1%
7.9731278545
< 0.1%
7.9661041715
< 0.1%
7.9541990785
< 0.1%
7.9322200145
< 0.1%

viral_load_wrhi003_category
Unsupported

Missing  Rejected  Unsupported 

Missing73125
Missing (%)100.0%
Memory size571.4 KiB

hemoglobin
Real number (ℝ)

Missing 

Distinct153
Distinct (%)0.8%
Missing53329
Missing (%)72.9%
Infinite0
Infinite (%)0.0%
Mean13.542158
Minimum1.7
Maximum153.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:08.955395image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1.7
5-th percentile10.3
Q112.4
median13.6
Q314.8
95-th percentile16.4
Maximum153.2
Range151.5
Interquartile range (IQR)2.4

Descriptive statistics

Standard deviation2.2185121
Coefficient of variation (CV)0.16382265
Kurtosis1050.3484
Mean13.542158
Median Absolute Deviation (MAD)1.2
Skewness17.814183
Sum268080.56
Variance4.9217961
MonotonicityNot monotonic
2025-12-02T18:32:09.003827image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13.5488
 
0.7%
13.4467
 
0.6%
13.9464
 
0.6%
13.3464
 
0.6%
13.1456
 
0.6%
13.6455
 
0.6%
13.7454
 
0.6%
13.8451
 
0.6%
14.1441
 
0.6%
12.9436
 
0.6%
Other values (143)15220
 
20.8%
(Missing)53329
72.9%
ValueCountFrequency (%)
1.71
< 0.1%
3.91
< 0.1%
4.11
< 0.1%
4.32
< 0.1%
4.41
< 0.1%
5.12
< 0.1%
5.22
< 0.1%
5.41
< 0.1%
5.61
< 0.1%
61
< 0.1%
ValueCountFrequency (%)
153.21
 
< 0.1%
1191
 
< 0.1%
23.51
 
< 0.1%
21.42
< 0.1%
20.61
 
< 0.1%
20.52
< 0.1%
203
< 0.1%
19.91
 
< 0.1%
19.82
< 0.1%
19.73
< 0.1%

hematocrit
Real number (ℝ)

Missing 

Distinct632
Distinct (%)3.6%
Missing55611
Missing (%)76.0%
Infinite0
Infinite (%)0.0%
Mean10.531625
Minimum0.144
Maximum60.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:09.051417image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.144
5-th percentile0.34
Q10.4
median0.44
Q328.8
95-th percentile44.1
Maximum60.3
Range60.156
Interquartile range (IQR)28.4

Descriptive statistics

Standard deviation17.289431
Coefficient of variation (CV)1.6416679
Kurtosis-0.47932718
Mean10.531625
Median Absolute Deviation (MAD)0.05
Skewness1.1818708
Sum184450.88
Variance298.92441
MonotonicityNot monotonic
2025-12-02T18:32:09.098134image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.43782
 
1.1%
0.42766
 
1.0%
0.41735
 
1.0%
0.4658
 
0.9%
0.44657
 
0.9%
0.45618
 
0.8%
0.46552
 
0.8%
0.39538
 
0.7%
0.47477
 
0.7%
0.38461
 
0.6%
Other values (622)11270
 
15.4%
(Missing)55611
76.0%
ValueCountFrequency (%)
0.1441
 
< 0.1%
0.1881
 
< 0.1%
0.1931
 
< 0.1%
0.21
 
< 0.1%
0.2031
 
< 0.1%
0.213
< 0.1%
0.2161
 
< 0.1%
0.2241
 
< 0.1%
0.2251
 
< 0.1%
0.233
< 0.1%
ValueCountFrequency (%)
60.31
< 0.1%
59.61
< 0.1%
57.81
< 0.1%
57.41
< 0.1%
56.71
< 0.1%
55.21
< 0.1%
55.11
< 0.1%
551
< 0.1%
54.71
< 0.1%
54.11
< 0.1%

rbc_count
Unsupported

Missing  Rejected  Unsupported 

Missing73125
Missing (%)100.0%
Memory size571.4 KiB

wbc_count
Unsupported

Missing  Rejected  Unsupported 

Missing73125
Missing (%)100.0%
Memory size571.4 KiB

platelet_count
Unsupported

Missing  Rejected  Unsupported 

Missing73125
Missing (%)100.0%
Memory size571.4 KiB

mcv
Real number (ℝ)

Missing 

Distinct545
Distinct (%)5.8%
Missing63684
Missing (%)87.1%
Infinite0
Infinite (%)0.0%
Mean90.786209
Minimum57
Maximum124.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:09.145559image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum57
5-th percentile77.6
Q186.6
median91.1
Q395.4
95-th percentile101.9
Maximum124.1
Range67.1
Interquartile range (IQR)8.8

Descriptive statistics

Standard deviation7.5369822
Coefficient of variation (CV)0.083019021
Kurtosis1.3785573
Mean90.786209
Median Absolute Deviation (MAD)4.4
Skewness-0.22165147
Sum857112.6
Variance56.8061
MonotonicityNot monotonic
2025-12-02T18:32:09.273893image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9186
 
0.1%
9075
 
0.1%
89.772
 
0.1%
8967
 
0.1%
91.866
 
0.1%
88.566
 
0.1%
91.764
 
0.1%
90.864
 
0.1%
9363
 
0.1%
93.263
 
0.1%
Other values (535)8755
 
12.0%
(Missing)63684
87.1%
ValueCountFrequency (%)
571
< 0.1%
581
< 0.1%
58.12
< 0.1%
592
< 0.1%
59.21
< 0.1%
59.61
< 0.1%
59.71
< 0.1%
601
< 0.1%
60.11
< 0.1%
60.51
< 0.1%
ValueCountFrequency (%)
124.11
< 0.1%
122.41
< 0.1%
1221
< 0.1%
121.11
< 0.1%
119.61
< 0.1%
119.41
< 0.1%
119.31
< 0.1%
119.11
< 0.1%
118.72
< 0.1%
117.91
< 0.1%

mch
Real number (ℝ)

Missing 

Distinct221
Distinct (%)2.4%
Missing64086
Missing (%)87.6%
Infinite0
Infinite (%)0.0%
Mean29.540325
Minimum15.2
Maximum42.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:09.317883image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum15.2
5-th percentile24.3
Q127.9
median29.7
Q331.3
95-th percentile33.6
Maximum42.6
Range27.4
Interquartile range (IQR)3.4

Descriptive statistics

Standard deviation2.8432652
Coefficient of variation (CV)0.096250301
Kurtosis1.3842879
Mean29.540325
Median Absolute Deviation (MAD)1.7
Skewness-0.31123393
Sum267015
Variance8.0841571
MonotonicityNot monotonic
2025-12-02T18:32:09.362564image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
29.3158
 
0.2%
30.6157
 
0.2%
29.8155
 
0.2%
29.9155
 
0.2%
30.5150
 
0.2%
30149
 
0.2%
31.1148
 
0.2%
29.6144
 
0.2%
28.6143
 
0.2%
31.2143
 
0.2%
Other values (211)7537
 
10.3%
(Missing)64086
87.6%
ValueCountFrequency (%)
15.21
< 0.1%
16.21
< 0.1%
16.71
< 0.1%
16.91
< 0.1%
17.31
< 0.1%
17.51
< 0.1%
17.62
< 0.1%
17.81
< 0.1%
17.91
< 0.1%
18.22
< 0.1%
ValueCountFrequency (%)
42.61
< 0.1%
41.51
< 0.1%
40.81
< 0.1%
40.61
< 0.1%
40.51
< 0.1%
40.41
< 0.1%
40.31
< 0.1%
39.91
< 0.1%
39.61
< 0.1%
39.51
< 0.1%

mchc
Real number (ℝ)

Missing 

Distinct90
Distinct (%)1.0%
Missing64086
Missing (%)87.6%
Infinite0
Infinite (%)0.0%
Mean32.471424
Minimum26.7
Maximum38.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:09.406707image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum26.7
5-th percentile30.8
Q131.8
median32.5
Q333.1
95-th percentile34.1
Maximum38.1
Range11.4
Interquartile range (IQR)1.3

Descriptive statistics

Standard deviation1.0308394
Coefficient of variation (CV)0.031746049
Kurtosis0.91104269
Mean32.471424
Median Absolute Deviation (MAD)0.7
Skewness-0.0076038562
Sum293509.2
Variance1.0626299
MonotonicityNot monotonic
2025-12-02T18:32:09.453054image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
32.6379
 
0.5%
32.8368
 
0.5%
32.4365
 
0.5%
32.5356
 
0.5%
32.7355
 
0.5%
32.9350
 
0.5%
32.3334
 
0.5%
33333
 
0.5%
32.1331
 
0.5%
32327
 
0.4%
Other values (80)5541
 
7.6%
(Missing)64086
87.6%
ValueCountFrequency (%)
26.71
< 0.1%
26.91
< 0.1%
27.51
< 0.1%
27.91
< 0.1%
28.31
< 0.1%
28.41
< 0.1%
28.51
< 0.1%
28.61
< 0.1%
28.72
< 0.1%
28.81
< 0.1%
ValueCountFrequency (%)
38.11
 
< 0.1%
37.31
 
< 0.1%
37.11
 
< 0.1%
36.71
 
< 0.1%
36.64
< 0.1%
36.51
 
< 0.1%
36.31
 
< 0.1%
36.23
< 0.1%
36.12
 
< 0.1%
367
< 0.1%

rdw
Real number (ℝ)

Missing 

Distinct155
Distinct (%)1.7%
Missing64088
Missing (%)87.6%
Infinite0
Infinite (%)0.0%
Mean14.557608
Minimum10.8
Maximum35.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:09.500190image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum10.8
5-th percentile12.6
Q113.4
median14.2
Q315.2
95-th percentile17.9
Maximum35.9
Range25.1
Interquartile range (IQR)1.8

Descriptive statistics

Standard deviation1.8481668
Coefficient of variation (CV)0.12695539
Kurtosis14.28462
Mean14.557608
Median Absolute Deviation (MAD)0.8
Skewness2.7566479
Sum131557.1
Variance3.4157204
MonotonicityNot monotonic
2025-12-02T18:32:09.548844image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13.8345
 
0.5%
13.9315
 
0.4%
13.7309
 
0.4%
13.4303
 
0.4%
13.6302
 
0.4%
13.3296
 
0.4%
13.5295
 
0.4%
14.2291
 
0.4%
14290
 
0.4%
13.2283
 
0.4%
Other values (145)6008
 
8.2%
(Missing)64088
87.6%
ValueCountFrequency (%)
10.81
 
< 0.1%
11.11
 
< 0.1%
11.31
 
< 0.1%
11.46
 
< 0.1%
11.52
 
< 0.1%
11.66
 
< 0.1%
11.75
 
< 0.1%
11.817
< 0.1%
11.921
< 0.1%
1219
< 0.1%
ValueCountFrequency (%)
35.91
< 0.1%
34.81
< 0.1%
30.31
< 0.1%
30.11
< 0.1%
301
< 0.1%
29.82
< 0.1%
29.31
< 0.1%
29.21
< 0.1%
28.82
< 0.1%
28.31
< 0.1%

neutrophils_pct
Unsupported

Missing  Rejected  Unsupported 

Missing73125
Missing (%)100.0%
Memory size571.4 KiB

lymphocytes_pct
Unsupported

Missing  Rejected  Unsupported 

Missing73125
Missing (%)100.0%
Memory size571.4 KiB

monocytes_pct
Unsupported

Missing  Rejected  Unsupported 

Missing73125
Missing (%)100.0%
Memory size571.4 KiB

eosinophils_pct
Unsupported

Missing  Rejected  Unsupported 

Missing73125
Missing (%)100.0%
Memory size571.4 KiB

basophils_pct
Unsupported

Missing  Rejected  Unsupported 

Missing73125
Missing (%)100.0%
Memory size571.4 KiB

fasting_glucose
Real number (ℝ)

Missing 

Distinct571
Distinct (%)7.9%
Missing65898
Missing (%)90.1%
Infinite0
Infinite (%)0.0%
Mean29.745861
Minimum0.2
Maximum345
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:09.594531image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.2
5-th percentile4
Q14.6
median5.1
Q376
95-th percentile96
Maximum345
Range344.8
Interquartile range (IQR)71.4

Descriptive statistics

Standard deviation38.924917
Coefficient of variation (CV)1.3085826
Kurtosis0.76422433
Mean29.745861
Median Absolute Deviation (MAD)0.78
Skewness1.1762677
Sum214973.34
Variance1515.1492
MonotonicityNot monotonic
2025-12-02T18:32:09.640948image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.7325
 
0.4%
4.6279
 
0.4%
4.8275
 
0.4%
4.5260
 
0.4%
4.4244
 
0.3%
4.3243
 
0.3%
4.9227
 
0.3%
5.1193
 
0.3%
5183
 
0.3%
4.2161
 
0.2%
Other values (561)4837
 
6.6%
(Missing)65898
90.1%
ValueCountFrequency (%)
0.21
< 0.1%
0.571
< 0.1%
0.821
< 0.1%
0.951
< 0.1%
1.121
< 0.1%
1.371
< 0.1%
1.471
< 0.1%
1.51
< 0.1%
1.811
< 0.1%
1.951
< 0.1%
ValueCountFrequency (%)
3451
< 0.1%
2991
< 0.1%
2951
< 0.1%
2741
< 0.1%
2251
< 0.1%
2201
< 0.1%
2171
< 0.1%
1921
< 0.1%
1901
< 0.1%
1682
< 0.1%

log10_fasting_glucose
Unsupported

Missing  Rejected  Unsupported 

Missing73125
Missing (%)100.0%
Memory size571.4 KiB

total_cholesterol
Real number (ℝ)

Missing 

Distinct2313
Distinct (%)30.8%
Missing65615
Missing (%)89.7%
Infinite0
Infinite (%)0.0%
Mean53.121437
Minimum1.12
Maximum363
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:09.688419image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1.12
5-th percentile2.97
Q13.9
median4.81
Q3129.1975
95-th percentile210
Maximum363
Range361.88
Interquartile range (IQR)125.2975

Descriptive statistics

Standard deviation79.686275
Coefficient of variation (CV)1.5000776
Kurtosis-0.099919211
Mean53.121437
Median Absolute Deviation (MAD)1.21
Skewness1.2056678
Sum398941.99
Variance6349.9024
MonotonicityNot monotonic
2025-12-02T18:32:09.735476image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.8145
 
0.2%
3.7137
 
0.2%
4.3134
 
0.2%
4133
 
0.2%
4.4126
 
0.2%
4.2122
 
0.2%
4.1117
 
0.2%
3.9113
 
0.2%
4.5107
 
0.1%
3.6104
 
0.1%
Other values (2303)6272
 
8.6%
(Missing)65615
89.7%
ValueCountFrequency (%)
1.121
 
< 0.1%
1.221
 
< 0.1%
1.291
 
< 0.1%
1.381
 
< 0.1%
1.41
 
< 0.1%
1.541
 
< 0.1%
1.591
 
< 0.1%
1.61
 
< 0.1%
1.85
< 0.1%
1.821
 
< 0.1%
ValueCountFrequency (%)
3631
< 0.1%
3391
< 0.1%
337.61
< 0.1%
3331
< 0.1%
330.641
< 0.1%
330.231
< 0.1%
321.071
< 0.1%
3211
< 0.1%
319.181
< 0.1%
317.571
< 0.1%

hdl_cholesterol
Real number (ℝ)

Missing 

Distinct1818
Distinct (%)24.2%
Missing65617
Missing (%)89.7%
Infinite0
Infinite (%)0.0%
Mean15.019969
Minimum0
Maximum368
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:09.780900image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.8
Q11.14
median1.5
Q332.54
95-th percentile61.2665
Maximum368
Range368
Interquartile range (IQR)31.4

Descriptive statistics

Standard deviation23.57598
Coefficient of variation (CV)1.5696424
Kurtosis8.1500262
Mean15.019969
Median Absolute Deviation (MAD)0.5
Skewness1.913957
Sum112769.93
Variance555.82685
MonotonicityNot monotonic
2025-12-02T18:32:09.828740image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.3331
 
0.5%
1.4287
 
0.4%
1.1279
 
0.4%
1.2268
 
0.4%
1256
 
0.4%
1.5242
 
0.3%
1.6196
 
0.3%
0.9188
 
0.3%
1.8137
 
0.2%
1.7133
 
0.2%
Other values (1808)5191
 
7.1%
(Missing)65617
89.7%
ValueCountFrequency (%)
01
 
< 0.1%
0.11
 
< 0.1%
0.181
 
< 0.1%
0.22
< 0.1%
0.281
 
< 0.1%
0.34
< 0.1%
0.321
 
< 0.1%
0.332
< 0.1%
0.342
< 0.1%
0.351
 
< 0.1%
ValueCountFrequency (%)
3681
< 0.1%
159.951
< 0.1%
157.431
< 0.1%
151.771
< 0.1%
150.691
< 0.1%
134.711
< 0.1%
133.21
< 0.1%
132.31
< 0.1%
122.731
< 0.1%
118.511
< 0.1%

ldl_cholesterol
Real number (ℝ)

Missing 

Distinct2225
Distinct (%)29.7%
Missing65641
Missing (%)89.8%
Infinite0
Infinite (%)0.0%
Mean31.209205
Minimum0
Maximum417
Zeros3
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:09.877115image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.14
Q12.01
median2.9
Q364.9
95-th percentile133.9595
Maximum417
Range417
Interquartile range (IQR)62.89

Descriptive statistics

Standard deviation49.186216
Coefficient of variation (CV)1.5760163
Kurtosis1.4014819
Mean31.209205
Median Absolute Deviation (MAD)1.14
Skewness1.5002327
Sum233569.69
Variance2419.2839
MonotonicityNot monotonic
2025-12-02T18:32:09.922668image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.2165
 
0.2%
2.3158
 
0.2%
2.6140
 
0.2%
2.7136
 
0.2%
2135
 
0.2%
2.1134
 
0.2%
2.4129
 
0.2%
2.5125
 
0.2%
1.9125
 
0.2%
1.6117
 
0.2%
Other values (2215)6120
 
8.4%
(Missing)65641
89.8%
ValueCountFrequency (%)
03
< 0.1%
0.031
 
< 0.1%
0.12
< 0.1%
0.141
 
< 0.1%
0.151
 
< 0.1%
0.181
 
< 0.1%
0.22
< 0.1%
0.211
 
< 0.1%
0.262
< 0.1%
0.271
 
< 0.1%
ValueCountFrequency (%)
4171
< 0.1%
268.91
< 0.1%
244.61
< 0.1%
242.431
< 0.1%
239.711
< 0.1%
233.231
< 0.1%
231.681
< 0.1%
2271
< 0.1%
2261
< 0.1%
224.191
< 0.1%

triglycerides
Real number (ℝ)

Missing 

Distinct2167
Distinct (%)32.9%
Missing66534
Missing (%)91.0%
Infinite0
Infinite (%)0.0%
Mean41.653541
Minimum0.05
Maximum1759.77
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:09.966029image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.05
5-th percentile0.5
Q10.8
median1.24
Q373.125
95-th percentile171.515
Maximum1759.77
Range1759.72
Interquartile range (IQR)72.325

Descriptive statistics

Standard deviation83.21337
Coefficient of variation (CV)1.9977502
Kurtosis72.952796
Mean41.653541
Median Absolute Deviation (MAD)0.64
Skewness5.9142824
Sum274538.49
Variance6924.4649
MonotonicityNot monotonic
2025-12-02T18:32:10.013146image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.8340
 
0.5%
0.6311
 
0.4%
0.9300
 
0.4%
0.7284
 
0.4%
1226
 
0.3%
1.1220
 
0.3%
0.5191
 
0.3%
1.2148
 
0.2%
1.3135
 
0.2%
1.4116
 
0.2%
Other values (2157)4320
 
5.9%
(Missing)66534
91.0%
ValueCountFrequency (%)
0.055
< 0.1%
0.062
 
< 0.1%
0.071
 
< 0.1%
0.081
 
< 0.1%
0.181
 
< 0.1%
0.21
 
< 0.1%
0.211
 
< 0.1%
0.221
 
< 0.1%
0.251
 
< 0.1%
0.262
 
< 0.1%
ValueCountFrequency (%)
1759.771
< 0.1%
1575.591
< 0.1%
1142.741
< 0.1%
1137.481
< 0.1%
1077.871
< 0.1%
9231
< 0.1%
9101
< 0.1%
8861
< 0.1%
873.341
< 0.1%
848.971
< 0.1%

creatinine
Real number (ℝ)

Missing 

Distinct218
Distinct (%)2.7%
Missing65195
Missing (%)89.2%
Infinite0
Infinite (%)0.0%
Mean38.304887
Minimum0.32
Maximum499
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:10.061472image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.32
5-th percentile0.57
Q10.79
median49
Q364
95-th percentile86
Maximum499
Range498.68
Interquartile range (IQR)63.21

Descriptive statistics

Standard deviation33.711855
Coefficient of variation (CV)0.8800928
Kurtosis3.3508582
Mean38.304887
Median Absolute Deviation (MAD)30
Skewness0.41947146
Sum303757.75
Variance1136.4891
MonotonicityNot monotonic
2025-12-02T18:32:10.109769image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.7313
 
0.4%
0.6268
 
0.4%
0.8262
 
0.4%
61156
 
0.2%
0.9152
 
0.2%
62149
 
0.2%
63147
 
0.2%
57145
 
0.2%
54138
 
0.2%
56135
 
0.2%
Other values (208)6065
 
8.3%
(Missing)65195
89.2%
ValueCountFrequency (%)
0.321
 
< 0.1%
0.341
 
< 0.1%
0.363
 
< 0.1%
0.382
 
< 0.1%
0.395
< 0.1%
0.410
< 0.1%
0.413
 
< 0.1%
0.429
< 0.1%
0.438
< 0.1%
0.444
 
< 0.1%
ValueCountFrequency (%)
4991
< 0.1%
2371
< 0.1%
2321
< 0.1%
2051
< 0.1%
1951
< 0.1%
1711
< 0.1%
1701
< 0.1%
1691
< 0.1%
1571
< 0.1%
1551
< 0.1%

creatinine_clearance
Real number (ℝ)

Missing 

Distinct438
Distinct (%)17.3%
Missing70598
Missing (%)96.5%
Infinite0
Infinite (%)0.0%
Mean114.62014
Minimum28
Maximum1320
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:10.155783image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum28
5-th percentile77.25
Q193
median108
Q3126
95-th percentile176
Maximum1320
Range1292
Interquartile range (IQR)33

Descriptive statistics

Standard deviation41.475193
Coefficient of variation (CV)0.36184908
Kurtosis313.26822
Mean114.62014
Median Absolute Deviation (MAD)16
Skewness12.116333
Sum289645.1
Variance1720.1916
MonotonicityNot monotonic
2025-12-02T18:32:10.206036image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9447
 
0.1%
10942
 
0.1%
9740
 
0.1%
9539
 
0.1%
11339
 
0.1%
11538
 
0.1%
9138
 
0.1%
10437
 
0.1%
9037
 
0.1%
10736
 
< 0.1%
Other values (428)2134
 
2.9%
(Missing)70598
96.5%
ValueCountFrequency (%)
281
 
< 0.1%
301
 
< 0.1%
311
 
< 0.1%
331
 
< 0.1%
401
 
< 0.1%
491
 
< 0.1%
501
 
< 0.1%
551
 
< 0.1%
581
 
< 0.1%
593
< 0.1%
ValueCountFrequency (%)
13201
< 0.1%
8111
< 0.1%
2601
< 0.1%
2561
< 0.1%
2461
< 0.1%
2451
< 0.1%
2432
< 0.1%
2391
< 0.1%
2381
< 0.1%
2371
< 0.1%

bun
Unsupported

Missing  Rejected  Unsupported 

Missing73125
Missing (%)100.0%
Memory size571.4 KiB

alt
Real number (ℝ)

Missing 

Distinct208
Distinct (%)2.0%
Missing62768
Missing (%)85.8%
Infinite0
Infinite (%)0.0%
Mean29.037057
Minimum1.1
Maximum1646
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:10.252803image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1.1
5-th percentile10
Q115
median21
Q331
95-th percentile63
Maximum1646
Range1644.9
Interquartile range (IQR)16

Descriptive statistics

Standard deviation47.024262
Coefficient of variation (CV)1.6194569
Kurtosis509.54977
Mean29.037057
Median Absolute Deviation (MAD)7
Skewness19.110594
Sum300736.8
Variance2211.2812
MonotonicityNot monotonic
2025-12-02T18:32:10.297780image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15475
 
0.6%
17467
 
0.6%
14457
 
0.6%
18453
 
0.6%
16444
 
0.6%
20430
 
0.6%
19424
 
0.6%
13412
 
0.6%
22374
 
0.5%
21366
 
0.5%
Other values (198)6055
 
8.3%
(Missing)62768
85.8%
ValueCountFrequency (%)
1.11
 
< 0.1%
44
 
< 0.1%
514
 
< 0.1%
631
 
< 0.1%
765
 
0.1%
8112
 
0.2%
9165
0.2%
10226
0.3%
11296
0.4%
12362
0.5%
ValueCountFrequency (%)
16462
< 0.1%
12702
< 0.1%
12482
< 0.1%
10601
< 0.1%
8311
< 0.1%
7601
< 0.1%
7302
< 0.1%
6251
< 0.1%
5891
< 0.1%
5382
< 0.1%

ast
Real number (ℝ)

Missing 

Distinct203
Distinct (%)2.0%
Missing62769
Missing (%)85.8%
Infinite0
Infinite (%)0.0%
Mean32.078196
Minimum2
Maximum1471
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:10.344467image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile16
Q121
median26
Q333
95-th percentile58.25
Maximum1471
Range1469
Interquartile range (IQR)12

Descriptive statistics

Standard deviation34.990886
Coefficient of variation (CV)1.0907997
Kurtosis489.53615
Mean32.078196
Median Absolute Deviation (MAD)6
Skewness17.159799
Sum332201.8
Variance1224.3621
MonotonicityNot monotonic
2025-12-02T18:32:10.392414image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
23565
 
0.8%
22555
 
0.8%
25546
 
0.7%
24527
 
0.7%
20499
 
0.7%
21479
 
0.7%
26476
 
0.7%
27438
 
0.6%
19421
 
0.6%
18405
 
0.6%
Other values (193)5445
 
7.4%
(Missing)62769
85.8%
ValueCountFrequency (%)
21
 
< 0.1%
3.61
 
< 0.1%
83
 
< 0.1%
92
 
< 0.1%
105
 
< 0.1%
119
 
< 0.1%
1233
 
< 0.1%
1371
0.1%
13.21
 
< 0.1%
1489
0.1%
ValueCountFrequency (%)
14711
< 0.1%
11691
< 0.1%
8871
< 0.1%
7151
< 0.1%
6522
< 0.1%
5451
< 0.1%
5401
< 0.1%
5342
< 0.1%
5141
< 0.1%
4651
< 0.1%

alp
Unsupported

Missing  Rejected  Unsupported 

Missing73125
Missing (%)100.0%
Memory size571.4 KiB

total_bilirubin
Real number (ℝ)

Missing 

Distinct202
Distinct (%)2.2%
Missing64078
Missing (%)87.6%
Infinite0
Infinite (%)0.0%
Mean3.0216072
Minimum0
Maximum94
Zeros6
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:10.440645image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.2
Q10.4
median2.6
Q34.6
95-th percentile8
Maximum94
Range94
Interquartile range (IQR)4.2

Descriptive statistics

Standard deviation3.9919683
Coefficient of variation (CV)1.3211407
Kurtosis130.65324
Mean3.0216072
Median Absolute Deviation (MAD)2.2
Skewness8.053527
Sum27336.48
Variance15.935811
MonotonicityNot monotonic
2025-12-02T18:32:10.484895image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.31011
 
1.4%
0.2982
 
1.3%
0.4747
 
1.0%
0.5410
 
0.6%
0.6234
 
0.3%
0.1225
 
0.3%
5216
 
0.3%
4164
 
0.2%
3155
 
0.2%
6146
 
0.2%
Other values (192)4757
 
6.5%
(Missing)64078
87.6%
ValueCountFrequency (%)
06
 
< 0.1%
0.1225
 
0.3%
0.2982
1.3%
0.31011
1.4%
0.4747
1.0%
0.5410
0.6%
0.6234
 
0.3%
0.7121
 
0.2%
0.883
 
0.1%
0.941
 
0.1%
ValueCountFrequency (%)
941
< 0.1%
89.51
< 0.1%
801
< 0.1%
77.41
< 0.1%
73.51
< 0.1%
691
< 0.1%
671
< 0.1%
61.11
< 0.1%
531
< 0.1%
511
< 0.1%

albumin
Real number (ℝ)

Missing 

Distinct300
Distinct (%)3.3%
Missing64067
Missing (%)87.6%
Infinite0
Infinite (%)0.0%
Mean38.989189
Minimum1.17
Maximum71.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:10.528449image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1.17
5-th percentile4.4
Q139
median42
Q344
95-th percentile47.6
Maximum71.3
Range70.13
Interquartile range (IQR)5

Descriptive statistics

Standard deviation10.62675
Coefficient of variation (CV)0.27255633
Kurtosis5.7472567
Mean38.989189
Median Absolute Deviation (MAD)3
Skewness-2.5283494
Sum353164.07
Variance112.92782
MonotonicityNot monotonic
2025-12-02T18:32:10.663002image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
43638
 
0.9%
41609
 
0.8%
42565
 
0.8%
40488
 
0.7%
45470
 
0.6%
44464
 
0.6%
39378
 
0.5%
46359
 
0.5%
38260
 
0.4%
47256
 
0.4%
Other values (290)4571
 
6.3%
(Missing)64067
87.6%
ValueCountFrequency (%)
1.171
 
< 0.1%
1.61
 
< 0.1%
1.71
 
< 0.1%
1.92
< 0.1%
21
 
< 0.1%
2.12
< 0.1%
2.24
< 0.1%
2.32
< 0.1%
2.43
< 0.1%
2.54
< 0.1%
ValueCountFrequency (%)
71.31
 
< 0.1%
601
 
< 0.1%
583
 
< 0.1%
57.21
 
< 0.1%
572
 
< 0.1%
561
 
< 0.1%
553
 
< 0.1%
546
< 0.1%
536
< 0.1%
5213
< 0.1%

total_protein
Unsupported

Missing  Rejected  Unsupported 

Missing73125
Missing (%)100.0%
Memory size571.4 KiB

sodium
Real number (ℝ)

Missing 

Distinct34
Distinct (%)0.4%
Missing64432
Missing (%)88.1%
Infinite0
Infinite (%)0.0%
Mean136.74037
Minimum110
Maximum150
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:10.710090image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum110
5-th percentile132
Q1135
median137
Q3139
95-th percentile141
Maximum150
Range40
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.0351713
Coefficient of variation (CV)0.022196601
Kurtosis3.853186
Mean136.74037
Median Absolute Deviation (MAD)2
Skewness-0.85651627
Sum1188684
Variance9.2122648
MonotonicityNot monotonic
2025-12-02T18:32:10.756343image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
1371304
 
1.8%
1361244
 
1.7%
1381169
 
1.6%
139977
 
1.3%
135971
 
1.3%
134671
 
0.9%
140661
 
0.9%
133385
 
0.5%
141371
 
0.5%
132225
 
0.3%
Other values (24)715
 
1.0%
(Missing)64432
88.1%
ValueCountFrequency (%)
1101
 
< 0.1%
1173
 
< 0.1%
1184
 
< 0.1%
1192
 
< 0.1%
1203
 
< 0.1%
1214
 
< 0.1%
1224
 
< 0.1%
1236
< 0.1%
12411
< 0.1%
1258
< 0.1%
ValueCountFrequency (%)
1501
 
< 0.1%
1482
 
< 0.1%
1471
 
< 0.1%
1467
 
< 0.1%
14520
 
< 0.1%
14436
 
< 0.1%
143101
 
0.1%
142181
 
0.2%
141371
0.5%
140661
0.9%

potassium
Real number (ℝ)

Missing 

Distinct50
Distinct (%)0.6%
Missing65017
Missing (%)88.9%
Infinite0
Infinite (%)0.0%
Mean4.2926394
Minimum1.05
Maximum6.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:10.801517image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1.05
5-th percentile3.7
Q14
median4.3
Q34.5
95-th percentile5
Maximum6.8
Range5.75
Interquartile range (IQR)0.5

Descriptive statistics

Standard deviation0.40458522
Coefficient of variation (CV)0.094250921
Kurtosis1.8516009
Mean4.2926394
Median Absolute Deviation (MAD)0.3
Skewness0.31081248
Sum34804.72
Variance0.1636892
MonotonicityNot monotonic
2025-12-02T18:32:10.846503image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.2922
 
1.3%
4.3898
 
1.2%
4.1791
 
1.1%
4.4787
 
1.1%
4705
 
1.0%
4.5605
 
0.8%
4.6530
 
0.7%
3.9517
 
0.7%
3.8412
 
0.6%
4.7411
 
0.6%
Other values (40)1530
 
2.1%
(Missing)65017
88.9%
ValueCountFrequency (%)
1.051
 
< 0.1%
2.11
 
< 0.1%
2.62
 
< 0.1%
2.71
 
< 0.1%
2.86
 
< 0.1%
2.822
 
< 0.1%
2.93
 
< 0.1%
33
 
< 0.1%
3.18
< 0.1%
3.218
< 0.1%
ValueCountFrequency (%)
6.81
 
< 0.1%
6.51
 
< 0.1%
6.43
 
< 0.1%
6.21
 
< 0.1%
6.11
 
< 0.1%
62
 
< 0.1%
5.92
 
< 0.1%
5.85
 
< 0.1%
5.713
< 0.1%
5.610
< 0.1%

calcium
Unsupported

Missing  Rejected  Unsupported 

Missing73125
Missing (%)100.0%
Memory size571.4 KiB

systolic_bp
Real number (ℝ)

Missing 

Distinct354
Distinct (%)0.9%
Missing34005
Missing (%)46.5%
Infinite0
Infinite (%)0.0%
Mean121.74479
Minimum72
Maximum258.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:10.893535image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum72
5-th percentile100
Q1111
median121
Q3131
95-th percentile145
Maximum258.5
Range186.5
Interquartile range (IQR)20

Descriptive statistics

Standard deviation14.141317
Coefficient of variation (CV)0.11615542
Kurtosis1.422209
Mean121.74479
Median Absolute Deviation (MAD)10
Skewness0.5373956
Sum4762656.2
Variance199.97683
MonotonicityNot monotonic
2025-12-02T18:32:10.942349image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1102439
 
3.3%
1201791
 
2.4%
1001210
 
1.7%
1301193
 
1.6%
1241041
 
1.4%
1211019
 
1.4%
122992
 
1.4%
129980
 
1.3%
128973
 
1.3%
118953
 
1.3%
Other values (344)26529
36.3%
(Missing)34005
46.5%
ValueCountFrequency (%)
721
 
< 0.1%
751
 
< 0.1%
782
 
< 0.1%
791
 
< 0.1%
8010
< 0.1%
813
 
< 0.1%
822
 
< 0.1%
835
< 0.1%
846
< 0.1%
856
< 0.1%
ValueCountFrequency (%)
258.51
< 0.1%
2391
< 0.1%
2201
< 0.1%
2151
< 0.1%
2131
< 0.1%
2111
< 0.1%
208.51
< 0.1%
207.51
< 0.1%
206.51
< 0.1%
2042
< 0.1%

diastolic_bp
Real number (ℝ)

Missing 

Distinct297
Distinct (%)0.8%
Missing34004
Missing (%)46.5%
Infinite0
Infinite (%)0.0%
Mean77.269766
Minimum7
Maximum662
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:10.988901image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile60
Q170
median77
Q384
95-th percentile94
Maximum662
Range655
Interquartile range (IQR)14

Descriptive statistics

Standard deviation10.98017
Coefficient of variation (CV)0.14210177
Kurtosis206.16591
Mean77.269766
Median Absolute Deviation (MAD)7
Skewness4.1735739
Sum3022870.5
Variance120.56414
MonotonicityNot monotonic
2025-12-02T18:32:11.036909image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
702851
 
3.9%
802254
 
3.1%
821455
 
2.0%
761308
 
1.8%
791306
 
1.8%
811296
 
1.8%
781283
 
1.8%
841272
 
1.7%
771264
 
1.7%
741255
 
1.7%
Other values (287)23577
32.2%
(Missing)34004
46.5%
ValueCountFrequency (%)
71
 
< 0.1%
121
 
< 0.1%
371
 
< 0.1%
381
 
< 0.1%
391
 
< 0.1%
402
 
< 0.1%
413
< 0.1%
424
< 0.1%
437
< 0.1%
43.666666671
 
< 0.1%
ValueCountFrequency (%)
6621
< 0.1%
1502
< 0.1%
1481
< 0.1%
141.51
< 0.1%
1361
< 0.1%
1341
< 0.1%
133.51
< 0.1%
1322
< 0.1%
131.51
< 0.1%
1311
< 0.1%

heart_rate
Real number (ℝ)

Missing 

Distinct216
Distinct (%)0.6%
Missing34517
Missing (%)47.2%
Infinite0
Infinite (%)0.0%
Mean75.072623
Minimum6
Maximum364
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:11.083089image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile56
Q166
median75
Q382.666667
95-th percentile96
Maximum364
Range358
Interquartile range (IQR)16.666667

Descriptive statistics

Standard deviation12.502762
Coefficient of variation (CV)0.16654223
Kurtosis8.3382324
Mean75.072623
Median Absolute Deviation (MAD)8
Skewness0.8141479
Sum2898403.8
Variance156.31905
MonotonicityNot monotonic
2025-12-02T18:32:11.131219image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
801926
 
2.6%
781398
 
1.9%
721371
 
1.9%
761354
 
1.9%
681309
 
1.8%
821259
 
1.7%
701193
 
1.6%
601130
 
1.5%
741125
 
1.5%
841094
 
1.5%
Other values (206)25449
34.8%
(Missing)34517
47.2%
ValueCountFrequency (%)
61
< 0.1%
141
< 0.1%
162
< 0.1%
171
< 0.1%
182
< 0.1%
201
< 0.1%
371
< 0.1%
392
< 0.1%
401
< 0.1%
411
< 0.1%
ValueCountFrequency (%)
3641
 
< 0.1%
1601
 
< 0.1%
1551
 
< 0.1%
1532
 
< 0.1%
1501
 
< 0.1%
1491
 
< 0.1%
1471
 
< 0.1%
1451
 
< 0.1%
1432
 
< 0.1%
1405
< 0.1%

temperature
Unsupported

Missing  Rejected  Unsupported 

Missing73125
Missing (%)100.0%
Memory size571.4 KiB

respiratory_rate
Real number (ℝ)

Missing 

Distinct31
Distinct (%)0.1%
Missing48313
Missing (%)66.1%
Infinite0
Infinite (%)0.0%
Mean16.860833
Minimum10
Maximum99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:11.174556image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile14
Q116
median17
Q318
95-th percentile20
Maximum99
Range89
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.3659282
Coefficient of variation (CV)0.14032095
Kurtosis123.90352
Mean16.860833
Median Absolute Deviation (MAD)1
Skewness4.6164714
Sum418351
Variance5.5976163
MonotonicityNot monotonic
2025-12-02T18:32:11.216470image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
186364
 
8.7%
165760
 
7.9%
142795
 
3.8%
202550
 
3.5%
152115
 
2.9%
172076
 
2.8%
191423
 
1.9%
13628
 
0.9%
12494
 
0.7%
21236
 
0.3%
Other values (21)371
 
0.5%
(Missing)48313
66.1%
ValueCountFrequency (%)
109
 
< 0.1%
1134
 
< 0.1%
12494
 
0.7%
13628
 
0.9%
142795
3.8%
152115
 
2.9%
165760
7.9%
172076
 
2.8%
186364
8.7%
191423
 
1.9%
ValueCountFrequency (%)
991
< 0.1%
801
< 0.1%
781
< 0.1%
761
< 0.1%
611
< 0.1%
571
< 0.1%
521
< 0.1%
421
< 0.1%
412
< 0.1%
332
< 0.1%

oxygen_saturation
Real number (ℝ)

Missing 

Distinct19
Distinct (%)0.1%
Missing57067
Missing (%)78.0%
Infinite0
Infinite (%)0.0%
Mean97.833665
Minimum17
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:11.254424image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum17
5-th percentile96
Q197
median98
Q399
95-th percentile100
Maximum100
Range83
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.5283891
Coefficient of variation (CV)0.015622322
Kurtosis505.5081
Mean97.833665
Median Absolute Deviation (MAD)1
Skewness-10.850448
Sum1571013
Variance2.3359731
MonotonicityNot monotonic
2025-12-02T18:32:11.291842image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
984582
 
6.3%
994506
 
6.2%
973174
 
4.3%
961957
 
2.7%
1001174
 
1.6%
95538
 
0.7%
9466
 
0.1%
9320
 
< 0.1%
9212
 
< 0.1%
918
 
< 0.1%
Other values (9)21
 
< 0.1%
(Missing)57067
78.0%
ValueCountFrequency (%)
171
 
< 0.1%
712
 
< 0.1%
751
 
< 0.1%
771
 
< 0.1%
801
 
< 0.1%
872
 
< 0.1%
882
 
< 0.1%
894
< 0.1%
907
< 0.1%
918
< 0.1%
ValueCountFrequency (%)
1001174
 
1.6%
994506
6.2%
984582
6.3%
973174
4.3%
961957
2.7%
95538
 
0.7%
9466
 
0.1%
9320
 
< 0.1%
9212
 
< 0.1%
918
 
< 0.1%

height_m
Real number (ℝ)

Missing 

Distinct55
Distinct (%)10.2%
Missing72586
Missing (%)99.3%
Infinite0
Infinite (%)0.0%
Mean1.6317996
Minimum1.01
Maximum1.94
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:11.334709image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1.01
5-th percentile1.5
Q11.57
median1.63
Q31.685
95-th percentile1.8
Maximum1.94
Range0.93
Interquartile range (IQR)0.115

Descriptive statistics

Standard deviation0.1031651
Coefficient of variation (CV)0.063221671
Kurtosis5.7614824
Mean1.6317996
Median Absolute Deviation (MAD)0.06
Skewness-1.0134457
Sum879.54
Variance0.010643038
MonotonicityNot monotonic
2025-12-02T18:32:11.380320image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.6553
 
0.1%
1.645
 
0.1%
1.730
 
< 0.1%
1.6730
 
< 0.1%
1.5730
 
< 0.1%
1.6827
 
< 0.1%
1.6324
 
< 0.1%
1.5821
 
< 0.1%
1.5919
 
< 0.1%
1.6219
 
< 0.1%
Other values (45)241
 
0.3%
(Missing)72586
99.3%
ValueCountFrequency (%)
1.011
 
< 0.1%
1.051
 
< 0.1%
1.151
 
< 0.1%
1.191
 
< 0.1%
1.21
 
< 0.1%
1.251
 
< 0.1%
1.371
 
< 0.1%
1.381
 
< 0.1%
1.43
< 0.1%
1.411
 
< 0.1%
ValueCountFrequency (%)
1.941
 
< 0.1%
1.912
 
< 0.1%
1.882
 
< 0.1%
1.871
 
< 0.1%
1.862
 
< 0.1%
1.851
 
< 0.1%
1.842
 
< 0.1%
1.835
< 0.1%
1.821
 
< 0.1%
1.813
< 0.1%

weight_kg
Real number (ℝ)

Missing 

Distinct905
Distinct (%)4.7%
Missing53787
Missing (%)73.6%
Infinite0
Infinite (%)0.0%
Mean71.346157
Minimum34
Maximum200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:11.424403image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum34
5-th percentile50.4
Q159.7
median68.6
Q380.5
95-th percentile101
Maximum200
Range166
Interquartile range (IQR)20.8

Descriptive statistics

Standard deviation15.844653
Coefficient of variation (CV)0.22208138
Kurtosis1.2894844
Mean71.346157
Median Absolute Deviation (MAD)10.2
Skewness0.91593816
Sum1379692
Variance251.05303
MonotonicityNot monotonic
2025-12-02T18:32:11.471878image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
60119
 
0.2%
6892
 
0.1%
6588
 
0.1%
5787
 
0.1%
7086
 
0.1%
6285
 
0.1%
6181
 
0.1%
5978
 
0.1%
8077
 
0.1%
7576
 
0.1%
Other values (895)18469
 
25.3%
(Missing)53787
73.6%
ValueCountFrequency (%)
342
< 0.1%
34.11
< 0.1%
34.61
< 0.1%
35.11
< 0.1%
35.31
< 0.1%
35.51
< 0.1%
35.82
< 0.1%
36.41
< 0.1%
371
< 0.1%
37.61
< 0.1%
ValueCountFrequency (%)
2001
< 0.1%
1711
< 0.1%
168.81
< 0.1%
162.21
< 0.1%
1541
< 0.1%
153.91
< 0.1%
1511
< 0.1%
1501
< 0.1%
147.21
< 0.1%
146.31
< 0.1%

bmi
Real number (ℝ)

Missing 

Distinct3548
Distinct (%)40.9%
Missing64455
Missing (%)88.1%
Infinite0
Infinite (%)0.0%
Mean26.831655
Minimum14
Maximum70.025559
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:11.517479image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum14
5-th percentile18.5
Q121.8
median25.449033
Q330.710886
95-th percentile39.4055
Maximum70.025559
Range56.025559
Interquartile range (IQR)8.9108864

Descriptive statistics

Standard deviation6.6371548
Coefficient of variation (CV)0.24736285
Kurtosis1.3039513
Mean26.831655
Median Absolute Deviation (MAD)4.1954115
Skewness0.99787835
Sum232630.45
Variance44.051824
MonotonicityNot monotonic
2025-12-02T18:32:11.563397image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21.534
 
< 0.1%
20.833
 
< 0.1%
20.328
 
< 0.1%
32.2098338228
 
< 0.1%
22.228
 
< 0.1%
20.528
 
< 0.1%
21.928
 
< 0.1%
2327
 
< 0.1%
2527
 
< 0.1%
19.926
 
< 0.1%
Other values (3538)8383
 
11.5%
(Missing)64455
88.1%
ValueCountFrequency (%)
141
< 0.1%
14.21
< 0.1%
14.71
< 0.1%
15.079670211
< 0.1%
15.11
< 0.1%
15.241
< 0.1%
15.269471081
< 0.1%
15.32
< 0.1%
15.338972351
< 0.1%
15.377500291
< 0.1%
ValueCountFrequency (%)
70.025559331
< 0.1%
67.296786391
< 0.1%
65.891
< 0.1%
64.099895941
< 0.1%
62.841
< 0.1%
60.386473431
< 0.1%
58.621
< 0.1%
571
< 0.1%
56.421
< 0.1%
56.11
< 0.1%

waist_circumference
Real number (ℝ)

Missing 

Distinct195
Distinct (%)12.4%
Missing71558
Missing (%)97.9%
Infinite0
Infinite (%)0.0%
Mean321.67863
Minimum0.6
Maximum9150
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:11.609064image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.6
5-th percentile0.76
Q10.92
median1.06
Q3792.5
95-th percentile1030
Maximum9150
Range9149.4
Interquartile range (IQR)791.58

Descriptive statistics

Standard deviation485.87768
Coefficient of variation (CV)1.5104444
Kurtosis67.939241
Mean321.67863
Median Absolute Deviation (MAD)0.23
Skewness4.3240911
Sum504070.42
Variance236077.12
MonotonicityNot monotonic
2025-12-02T18:32:11.653029image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
143
 
0.1%
0.9341
 
0.1%
0.9631
 
< 0.1%
0.9730
 
< 0.1%
0.8827
 
< 0.1%
0.9227
 
< 0.1%
1.0327
 
< 0.1%
0.927
 
< 0.1%
0.9527
 
< 0.1%
0.9425
 
< 0.1%
Other values (185)1262
 
1.7%
(Missing)71558
97.9%
ValueCountFrequency (%)
0.61
 
< 0.1%
0.622
 
< 0.1%
0.631
 
< 0.1%
0.651
 
< 0.1%
0.663
 
< 0.1%
0.671
 
< 0.1%
0.683
 
< 0.1%
0.698
< 0.1%
0.78
< 0.1%
0.718
< 0.1%
ValueCountFrequency (%)
91501
< 0.1%
15101
< 0.1%
14501
< 0.1%
14351
< 0.1%
14001
< 0.1%
13301
< 0.1%
13101
< 0.1%
13001
< 0.1%
12951
< 0.1%
12802
< 0.1%

temp_mean_c
Real number (ℝ)

Missing 

Distinct296
Distinct (%)33.3%
Missing72237
Missing (%)98.8%
Infinite0
Infinite (%)0.0%
Mean14.503477
Minimum4.9788208
Maximum26.32251
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:11.697141image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum4.9788208
5-th percentile8.0166565
Q112.157227
median14.003479
Q316.490295
95-th percentile21.866541
Maximum26.32251
Range21.343689
Interquartile range (IQR)4.3330688

Descriptive statistics

Standard deviation4.0426477
Coefficient of variation (CV)0.27873644
Kurtosis-0.074260038
Mean14.503477
Median Absolute Deviation (MAD)2.2520447
Skewness0.24395347
Sum12879.088
Variance16.343001
MonotonicityNot monotonic
2025-12-02T18:32:11.743308image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16.0229492225
 
< 0.1%
14.5228271524
 
< 0.1%
16.4902954124
 
< 0.1%
13.732116723
 
< 0.1%
14.7912597722
 
< 0.1%
13.0095214818
 
< 0.1%
12.4013061518
 
< 0.1%
13.7526245118
 
< 0.1%
14.5086059614
 
< 0.1%
12.1572265613
 
< 0.1%
Other values (286)689
 
0.9%
(Missing)72237
98.8%
ValueCountFrequency (%)
4.9788208016
< 0.1%
5.1090087891
 
< 0.1%
5.4556884771
 
< 0.1%
5.7221679692
 
< 0.1%
6.0021057131
 
< 0.1%
6.1203613282
 
< 0.1%
6.3478088381
 
< 0.1%
6.3999938963
< 0.1%
6.5618286131
 
< 0.1%
6.5851135252
 
< 0.1%
ValueCountFrequency (%)
26.322509772
< 0.1%
26.010040282
< 0.1%
24.825622562
< 0.1%
24.110717773
< 0.1%
23.954925542
< 0.1%
23.510437012
< 0.1%
23.330627441
 
< 0.1%
23.309844974
< 0.1%
23.247985842
< 0.1%
22.817352291
 
< 0.1%

temp_max_c
Real number (ℝ)

Missing 

Distinct296
Distinct (%)33.3%
Missing72237
Missing (%)98.8%
Infinite0
Infinite (%)0.0%
Mean21.966913
Minimum9.5418701
Maximum36.241394
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:11.788775image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum9.5418701
5-th percentile14.266785
Q119.648193
median22.58963
Q324.063721
95-th percentile28.567322
Maximum36.241394
Range26.699524
Interquartile range (IQR)4.4155273

Descriptive statistics

Standard deviation4.1913155
Coefficient of variation (CV)0.1908013
Kurtosis0.40134385
Mean21.966913
Median Absolute Deviation (MAD)2.315094
Skewness-0.23473885
Sum19506.619
Variance17.567126
MonotonicityNot monotonic
2025-12-02T18:32:11.837157image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24.1762390125
 
< 0.1%
23.1662292524
 
< 0.1%
22.7756347724
 
< 0.1%
23.3603210423
 
< 0.1%
23.0399780322
 
< 0.1%
17.5289611818
 
< 0.1%
15.0956726118
 
< 0.1%
21.3818054218
 
< 0.1%
23.3358154314
 
< 0.1%
20.2586975113
 
< 0.1%
Other values (286)689
 
0.9%
(Missing)72237
98.8%
ValueCountFrequency (%)
9.5418701171
 
< 0.1%
10.096374511
 
< 0.1%
10.154022222
 
< 0.1%
10.54254152
 
< 0.1%
11.053436282
 
< 0.1%
11.095214846
< 0.1%
11.2534795
< 0.1%
11.426605221
 
< 0.1%
12.546325682
 
< 0.1%
13.318603522
 
< 0.1%
ValueCountFrequency (%)
36.241394042
< 0.1%
33.421691892
< 0.1%
32.3003543
< 0.1%
31.345581052
< 0.1%
30.71719362
< 0.1%
30.394927982
< 0.1%
30.235473631
 
< 0.1%
30.121734623
< 0.1%
30.062103274
< 0.1%
29.974945071
 
< 0.1%

temp_min_c
Real number (ℝ)

Missing 

Distinct296
Distinct (%)33.3%
Missing72237
Missing (%)98.8%
Infinite0
Infinite (%)0.0%
Mean8.1055112
Minimum-1.4849548
Maximum19.463043
Zeros0
Zeros (%)0.0%
Negative26
Negative (%)< 0.1%
Memory size571.4 KiB
2025-12-02T18:32:11.885106image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum-1.4849548
5-th percentile1.4329224
Q15.2141113
median7.456543
Q310.378067
95-th percentile16.693787
Maximum19.463043
Range20.947998
Interquartile range (IQR)5.1639557

Descriptive statistics

Standard deviation4.5279855
Coefficient of variation (CV)0.55863046
Kurtosis-0.31371425
Mean8.1055112
Median Absolute Deviation (MAD)2.7251282
Skewness0.44596746
Sum7197.6939
Variance20.502652
MonotonicityNot monotonic
2025-12-02T18:32:11.930077image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.01800537125
 
< 0.1%
7.66375732424
 
< 0.1%
9.76635742224
 
< 0.1%
5.75115966823
 
< 0.1%
7.75796508822
 
< 0.1%
7.41940307618
 
< 0.1%
10.3723754918
 
< 0.1%
6.82806396518
 
< 0.1%
6.42950439514
 
< 0.1%
5.21411132813
 
< 0.1%
Other values (286)689
 
0.9%
(Missing)72237
98.8%
ValueCountFrequency (%)
-1.4849548341
 
< 0.1%
-1.4693908691
 
< 0.1%
-1.3090820311
 
< 0.1%
-0.9263610841
 
< 0.1%
-0.79959106456
< 0.1%
-0.55575561524
< 0.1%
-0.2720642094
< 0.1%
-0.10504150391
 
< 0.1%
-0.075500488281
 
< 0.1%
-0.074035644536
< 0.1%
ValueCountFrequency (%)
19.463043212
 
< 0.1%
19.118103033
< 0.1%
19.0347292
 
< 0.1%
18.972320562
 
< 0.1%
18.831359862
 
< 0.1%
18.687042241
 
< 0.1%
18.189208981
 
< 0.1%
18.044433591
 
< 0.1%
18.015777595
< 0.1%
17.972686772
 
< 0.1%

temp_range_c
Real number (ℝ)

Missing 

Distinct295
Distinct (%)33.2%
Missing72237
Missing (%)98.8%
Infinite0
Infinite (%)0.0%
Mean13.861402
Minimum2.9534912
Maximum21.440765
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:11.975332image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum2.9534912
5-th percentile7.4714859
Q112.209167
median14.553741
Q316.158234
95-th percentile17.825395
Maximum21.440765
Range18.487274
Interquartile range (IQR)3.9490662

Descriptive statistics

Standard deviation3.2813658
Coefficient of variation (CV)0.23672683
Kurtosis0.8729343
Mean13.861402
Median Absolute Deviation (MAD)1.9451141
Skewness-0.92373391
Sum12308.925
Variance10.767362
MonotonicityNot monotonic
2025-12-02T18:32:12.110916image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16.1582336425
 
< 0.1%
13.0092773424
 
< 0.1%
15.5024719224
 
< 0.1%
17.6091613823
 
< 0.1%
15.2820129422
 
< 0.1%
10.1095581118
 
< 0.1%
4.72329711918
 
< 0.1%
14.5537414618
 
< 0.1%
16.9063110414
 
< 0.1%
15.0445861813
 
< 0.1%
Other values (285)689
 
0.9%
(Missing)72237
98.8%
ValueCountFrequency (%)
2.9534912112
 
< 0.1%
3.4290771481
 
< 0.1%
4.2478027341
 
< 0.1%
4.4655151375
 
< 0.1%
4.5126953122
 
< 0.1%
4.6085205082
 
< 0.1%
4.72329711918
< 0.1%
5.0881652831
 
< 0.1%
5.4954833981
 
< 0.1%
5.6801452641
 
< 0.1%
ValueCountFrequency (%)
21.440765381
 
< 0.1%
20.665496831
 
< 0.1%
20.448425292
 
< 0.1%
20.210449222
 
< 0.1%
19.796142584
< 0.1%
19.298370361
 
< 0.1%
19.043151867
< 0.1%
18.962524417
< 0.1%
18.761932371
 
< 0.1%
18.678741463
< 0.1%

temp_lag1d
Real number (ℝ)

Missing 

Distinct296
Distinct (%)33.3%
Missing72237
Missing (%)98.8%
Infinite0
Infinite (%)0.0%
Mean14.503477
Minimum4.9788208
Maximum26.32251
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:12.160057image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum4.9788208
5-th percentile8.0166565
Q112.157227
median14.003479
Q316.490295
95-th percentile21.866541
Maximum26.32251
Range21.343689
Interquartile range (IQR)4.3330688

Descriptive statistics

Standard deviation4.0426477
Coefficient of variation (CV)0.27873644
Kurtosis-0.074260038
Mean14.503477
Median Absolute Deviation (MAD)2.2520447
Skewness0.24395347
Sum12879.088
Variance16.343001
MonotonicityNot monotonic
2025-12-02T18:32:12.204532image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16.0229492225
 
< 0.1%
14.5228271524
 
< 0.1%
16.4902954124
 
< 0.1%
13.732116723
 
< 0.1%
14.7912597722
 
< 0.1%
13.0095214818
 
< 0.1%
12.4013061518
 
< 0.1%
13.7526245118
 
< 0.1%
14.5086059614
 
< 0.1%
12.1572265613
 
< 0.1%
Other values (286)689
 
0.9%
(Missing)72237
98.8%
ValueCountFrequency (%)
4.9788208016
< 0.1%
5.1090087891
 
< 0.1%
5.4556884771
 
< 0.1%
5.7221679692
 
< 0.1%
6.0021057131
 
< 0.1%
6.1203613282
 
< 0.1%
6.3478088381
 
< 0.1%
6.3999938963
< 0.1%
6.5618286131
 
< 0.1%
6.5851135252
 
< 0.1%
ValueCountFrequency (%)
26.322509772
< 0.1%
26.010040282
< 0.1%
24.825622562
< 0.1%
24.110717773
< 0.1%
23.954925542
< 0.1%
23.510437012
< 0.1%
23.330627441
 
< 0.1%
23.309844974
< 0.1%
23.247985842
< 0.1%
22.817352291
 
< 0.1%

temp_lag3d
Real number (ℝ)

Missing 

Distinct296
Distinct (%)33.3%
Missing72237
Missing (%)98.8%
Infinite0
Infinite (%)0.0%
Mean14.582194
Minimum6.528066
Maximum25.396169
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:12.248096image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum6.528066
5-th percentile8.5402222
Q112.411395
median14.109039
Q316.693186
95-th percentile21.307429
Maximum25.396169
Range18.868103
Interquartile range (IQR)4.2817917

Descriptive statistics

Standard deviation3.8480293
Coefficient of variation (CV)0.26388548
Kurtosis-0.36058754
Mean14.582194
Median Absolute Deviation (MAD)2.2449646
Skewness0.30674608
Sum12948.988
Variance14.807329
MonotonicityNot monotonic
2025-12-02T18:32:12.295689image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15.0413004625
 
< 0.1%
15.0511881524
 
< 0.1%
16.6931864424
 
< 0.1%
14.7592976923
 
< 0.1%
14.1090393122
 
< 0.1%
13.0794270818
 
< 0.1%
13.8919474318
 
< 0.1%
13.0544840518
 
< 0.1%
14.2148539214
 
< 0.1%
13.3389587413
 
< 0.1%
Other values (286)689
 
0.9%
(Missing)72237
98.8%
ValueCountFrequency (%)
6.5280659993
< 0.1%
6.8114624021
 
< 0.1%
7.0124003092
 
< 0.1%
7.1034037271
 
< 0.1%
7.1181030271
 
< 0.1%
7.2067871096
< 0.1%
7.2213541671
 
< 0.1%
7.3287963871
 
< 0.1%
7.5240275072
 
< 0.1%
7.5711059571
 
< 0.1%
ValueCountFrequency (%)
25.396169032
< 0.1%
24.631988532
< 0.1%
24.161946612
< 0.1%
24.112386071
 
< 0.1%
23.511179611
 
< 0.1%
23.117909752
< 0.1%
22.915334071
 
< 0.1%
22.605407713
< 0.1%
22.550638832
< 0.1%
22.489969892
< 0.1%

temp_lag7d
Real number (ℝ)

Missing 

Distinct296
Distinct (%)33.3%
Missing72237
Missing (%)98.8%
Infinite0
Infinite (%)0.0%
Mean14.666129
Minimum6.8862043
Maximum24.436964
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:12.342558image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum6.8862043
5-th percentile8.4798226
Q112.32496
median14.404454
Q316.525761
95-th percentile21.399849
Maximum24.436964
Range17.550759
Interquartile range (IQR)4.2008013

Descriptive statistics

Standard deviation3.698337
Coefficient of variation (CV)0.25216858
Kurtosis-0.40421102
Mean14.666129
Median Absolute Deviation (MAD)2.0794939
Skewness0.27711551
Sum13023.522
Variance13.677696
MonotonicityNot monotonic
2025-12-02T18:32:12.389268image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14.1935250425
 
< 0.1%
14.4965994724
 
< 0.1%
16.3932800324
 
< 0.1%
14.5998273623
 
< 0.1%
14.5676923522
 
< 0.1%
14.7955496718
 
< 0.1%
15.2570626418
 
< 0.1%
14.4044538218
 
< 0.1%
14.2324218814
 
< 0.1%
13.9023873513
 
< 0.1%
Other values (286)689
 
0.9%
(Missing)72237
98.8%
ValueCountFrequency (%)
6.8862043111
 
< 0.1%
7.0244663782
 
< 0.1%
7.4827270512
 
< 0.1%
7.5019182486
< 0.1%
7.712829591
 
< 0.1%
7.7578996934
< 0.1%
7.9348798481
 
< 0.1%
7.9836556571
 
< 0.1%
7.9928806853
< 0.1%
8.0571289064
< 0.1%
ValueCountFrequency (%)
24.436963761
 
< 0.1%
24.201974052
 
< 0.1%
23.839760921
 
< 0.1%
23.568429133
< 0.1%
22.42340962
 
< 0.1%
22.321358821
 
< 0.1%
22.040073945
< 0.1%
22.023053851
 
< 0.1%
21.994349895
< 0.1%
21.945691791
 
< 0.1%

temp_lag14d
Real number (ℝ)

Missing 

Distinct296
Distinct (%)33.3%
Missing72237
Missing (%)98.8%
Infinite0
Infinite (%)0.0%
Mean14.850526
Minimum7.8528551
Maximum22.647117
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:12.434261image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum7.8528551
5-th percentile9.2700983
Q112.169412
median14.644039
Q317.332783
95-th percentile21.334483
Maximum22.647117
Range14.794261
Interquartile range (IQR)5.1633704

Descriptive statistics

Standard deviation3.6310447
Coefficient of variation (CV)0.24450614
Kurtosis-0.71471804
Mean14.850526
Median Absolute Deviation (MAD)2.4789145
Skewness0.27508636
Sum13187.267
Variance13.184486
MonotonicityNot monotonic
2025-12-02T18:32:12.482393image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15.0787113725
 
< 0.1%
14.8768310524
 
< 0.1%
16.6653573224
 
< 0.1%
14.6976885123
 
< 0.1%
14.3957672122
 
< 0.1%
15.4622911718
 
< 0.1%
15.6296452118
 
< 0.1%
15.3988669318
 
< 0.1%
14.3645106714
 
< 0.1%
14.2350398513
 
< 0.1%
Other values (286)689
 
0.9%
(Missing)72237
98.8%
ValueCountFrequency (%)
7.8528551373
< 0.1%
7.8856070381
 
< 0.1%
8.0611921041
 
< 0.1%
8.0651899071
 
< 0.1%
8.1053030834
< 0.1%
8.2836957662
< 0.1%
8.3356584821
 
< 0.1%
8.3383680072
< 0.1%
8.4118630552
< 0.1%
8.4265093122
< 0.1%
ValueCountFrequency (%)
22.647116523
< 0.1%
22.23191181
 
< 0.1%
22.049617225
< 0.1%
22.043145321
 
< 0.1%
21.984141761
 
< 0.1%
21.935001922
 
< 0.1%
21.898411341
 
< 0.1%
21.838437762
 
< 0.1%
21.76813182
 
< 0.1%
21.737934661
 
< 0.1%

temp_lag21d
Real number (ℝ)

Missing 

Distinct296
Distinct (%)33.3%
Missing72237
Missing (%)98.8%
Infinite0
Infinite (%)0.0%
Mean14.971551
Minimum8.2628421
Maximum21.927034
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:12.527763image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum8.2628421
5-th percentile9.5275522
Q112.289772
median15.073832
Q317.250674
95-th percentile21.208546
Maximum21.927034
Range13.664192
Interquartile range (IQR)4.9609026

Descriptive statistics

Standard deviation3.5603356
Coefficient of variation (CV)0.23780672
Kurtosis-0.83935337
Mean14.971551
Median Absolute Deviation (MAD)2.5709882
Skewness0.21728168
Sum13294.738
Variance12.67599
MonotonicityNot monotonic
2025-12-02T18:32:12.573230image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15.3528892925
 
< 0.1%
15.251963324
 
< 0.1%
16.5254865424
 
< 0.1%
15.1748032323
 
< 0.1%
15.0738321922
 
< 0.1%
16.0347609718
 
< 0.1%
16.199288518
 
< 0.1%
15.9117228218
 
< 0.1%
14.6620279914
 
< 0.1%
14.2313072613
 
< 0.1%
Other values (286)689
 
0.9%
(Missing)72237
98.8%
ValueCountFrequency (%)
8.2628420881
 
< 0.1%
8.4567507792
< 0.1%
8.478070941
 
< 0.1%
8.5375148233
< 0.1%
8.5759306411
 
< 0.1%
8.7832539881
 
< 0.1%
8.7887892952
< 0.1%
8.7917567661
 
< 0.1%
8.795285184
< 0.1%
8.7960074291
 
< 0.1%
ValueCountFrequency (%)
21.927033922
< 0.1%
21.919953851
 
< 0.1%
21.804873511
 
< 0.1%
21.749702092
< 0.1%
21.691849482
< 0.1%
21.665245421
 
< 0.1%
21.664754231
 
< 0.1%
21.656840011
 
< 0.1%
21.656095963
< 0.1%
21.634815031
 
< 0.1%

temp_lag30d
Real number (ℝ)

Missing 

Distinct296
Distinct (%)33.3%
Missing72237
Missing (%)98.8%
Infinite0
Infinite (%)0.0%
Mean15.176459
Minimum8.5436798
Maximum21.773014
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:12.620484image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum8.5436798
5-th percentile9.8961349
Q112.162722
median15.584126
Q317.198543
95-th percentile21.25174
Maximum21.773014
Range13.229335
Interquartile range (IQR)5.0358215

Descriptive statistics

Standard deviation3.5118803
Coefficient of variation (CV)0.23140314
Kurtosis-0.90352245
Mean15.176459
Median Absolute Deviation (MAD)2.6350779
Skewness0.13540262
Sum13476.696
Variance12.333303
MonotonicityNot monotonic
2025-12-02T18:32:12.668191image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15.9846557625
 
< 0.1%
15.9281972224
 
< 0.1%
17.0995076524
 
< 0.1%
15.7779968323
 
< 0.1%
15.5841257722
 
< 0.1%
16.2393239318
 
< 0.1%
16.4506805418
 
< 0.1%
16.070200618
 
< 0.1%
15.1880910214
 
< 0.1%
14.8194193513
 
< 0.1%
Other values (286)689
 
0.9%
(Missing)72237
98.8%
ValueCountFrequency (%)
8.543679811
 
< 0.1%
8.574196372
< 0.1%
8.574885053
< 0.1%
8.6541595461
 
< 0.1%
8.7336120611
 
< 0.1%
8.9447875982
< 0.1%
8.9921010341
 
< 0.1%
9.0136322021
 
< 0.1%
9.1092895511
 
< 0.1%
9.1409667972
< 0.1%
ValueCountFrequency (%)
21.773014323
< 0.1%
21.744408161
 
< 0.1%
21.678329471
 
< 0.1%
21.605676271
 
< 0.1%
21.540588382
< 0.1%
21.505571491
 
< 0.1%
21.490803022
< 0.1%
21.440364582
< 0.1%
21.436776731
 
< 0.1%
21.431310021
 
< 0.1%

temp_variability_7d
Real number (ℝ)

Missing 

Distinct296
Distinct (%)33.3%
Missing72237
Missing (%)98.8%
Infinite0
Infinite (%)0.0%
Mean1.3868453
Minimum0.32363731
Maximum6.1832705
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:12.714008image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.32363731
5-th percentile0.44317504
Q10.81322763
median1.2300129
Q31.689106
95-th percentile2.8294958
Maximum6.1832705
Range5.8596332
Interquartile range (IQR)0.87587834

Descriptive statistics

Standard deviation0.79131031
Coefficient of variation (CV)0.57058297
Kurtosis6.6663669
Mean1.3868453
Median Absolute Deviation (MAD)0.44061814
Skewness1.8258614
Sum1231.5186
Variance0.626172
MonotonicityNot monotonic
2025-12-02T18:32:12.756708image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.23693284825
 
< 0.1%
0.951615274424
 
< 0.1%
0.461873634424
 
< 0.1%
0.788656111923
 
< 0.1%
0.759247171122
 
< 0.1%
1.68910597118
 
< 0.1%
1.55586947118
 
< 0.1%
1.54182315918
 
< 0.1%
0.419463158814
 
< 0.1%
0.914953613213
 
< 0.1%
Other values (286)689
 
0.9%
(Missing)72237
98.8%
ValueCountFrequency (%)
0.32363731112
 
< 0.1%
0.36020526832
 
< 0.1%
0.36845133051
 
< 0.1%
0.376259914212
< 0.1%
0.419463158814
< 0.1%
0.42105516934
 
< 0.1%
0.442142023510
< 0.1%
0.4450934934
 
< 0.1%
0.461873634424
< 0.1%
0.47723938661
 
< 0.1%
ValueCountFrequency (%)
6.1832705385
< 0.1%
3.8195237662
 
< 0.1%
3.6984456283
< 0.1%
3.5672119771
 
< 0.1%
3.3449205111
 
< 0.1%
3.2886902752
 
< 0.1%
3.1483729681
 
< 0.1%
3.1350332291
 
< 0.1%
3.1212111022
 
< 0.1%
3.0141222452
 
< 0.1%

temp_variability_30d
Real number (ℝ)

Missing 

Distinct296
Distinct (%)33.3%
Missing72237
Missing (%)98.8%
Infinite0
Infinite (%)0.0%
Mean1.9550827
Minimum0.93819037
Maximum4.5627344
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:12.801766image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.93819037
5-th percentile1.2130117
Q11.5969549
median1.7942443
Q32.2763114
95-th percentile2.8580624
Maximum4.5627344
Range3.624544
Interquartile range (IQR)0.67935649

Descriptive statistics

Standard deviation0.55233943
Coefficient of variation (CV)0.28251462
Kurtosis2.4626191
Mean1.9550827
Median Absolute Deviation (MAD)0.31596297
Skewness1.1489426
Sum1736.1134
Variance0.30507885
MonotonicityNot monotonic
2025-12-02T18:32:12.849752image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.59342111825
 
< 0.1%
1.61478364624
 
< 0.1%
1.79424431624
 
< 0.1%
1.60202933923
 
< 0.1%
1.58656235922
 
< 0.1%
1.73517653518
 
< 0.1%
1.71424247818
 
< 0.1%
1.72154012718
 
< 0.1%
1.40243656314
 
< 0.1%
1.29977630213
 
< 0.1%
Other values (286)689
 
0.9%
(Missing)72237
98.8%
ValueCountFrequency (%)
0.93819037474
< 0.1%
1.0175004551
 
< 0.1%
1.0261240022
< 0.1%
1.0351881291
 
< 0.1%
1.0356315421
 
< 0.1%
1.0365910222
< 0.1%
1.0484977342
< 0.1%
1.049342791
 
< 0.1%
1.1061961381
 
< 0.1%
1.1116992332
< 0.1%
ValueCountFrequency (%)
4.5627343965
< 0.1%
3.9733862122
 
< 0.1%
3.8054400561
 
< 0.1%
3.7443253642
 
< 0.1%
3.6688243181
 
< 0.1%
3.614309732
 
< 0.1%
3.5323425241
 
< 0.1%
3.4202057811
 
< 0.1%
3.2731386931
 
< 0.1%
3.2337092462
 
< 0.1%

apparent_temp
Real number (ℝ)

Missing 

Distinct296
Distinct (%)33.3%
Missing72237
Missing (%)98.8%
Infinite0
Infinite (%)0.0%
Mean26.833529
Minimum8.2246424
Maximum53.466557
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:12.899321image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum8.2246424
5-th percentile14.642363
Q122.783892
median27.608551
Q330.125997
95-th percentile38.229124
Maximum53.466557
Range45.241915
Interquartile range (IQR)7.3421048

Descriptive statistics

Standard deviation6.9327427
Coefficient of variation (CV)0.2583612
Kurtosis0.44204015
Mean26.833529
Median Absolute Deviation (MAD)3.8270046
Skewness0.039399906
Sum23828.174
Variance48.062922
MonotonicityNot monotonic
2025-12-02T18:32:12.945715image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30.3208867325
 
< 0.1%
28.5853467924
 
< 0.1%
27.922542924
 
< 0.1%
28.9164394923
 
< 0.1%
28.3705991522
 
< 0.1%
19.4719339618
 
< 0.1%
15.8386523418
 
< 0.1%
25.5953931118
 
< 0.1%
28.8745728514
 
< 0.1%
23.7634921413
 
< 0.1%
Other values (286)689
 
0.9%
(Missing)72237
98.8%
ValueCountFrequency (%)
8.2246423621
 
< 0.1%
8.9424289721
 
< 0.1%
9.0175918412
 
< 0.1%
9.526807532
 
< 0.1%
10.2034462
 
< 0.1%
10.259131586
< 0.1%
10.470562215
< 0.1%
10.702725391
 
< 0.1%
12.226425142
 
< 0.1%
13.299685452
 
< 0.1%
ValueCountFrequency (%)
53.46655692
< 0.1%
47.658406932
< 0.1%
45.416238773
< 0.1%
43.537452982
< 0.1%
42.316143982
< 0.1%
41.694488612
< 0.1%
41.388073941
 
< 0.1%
41.169983333
< 0.1%
41.055800464
< 0.1%
40.889104581
 
< 0.1%

temp_anomaly
Real number (ℝ)

Missing 

Distinct296
Distinct (%)33.3%
Missing72237
Missing (%)98.8%
Infinite0
Infinite (%)0.0%
Mean-0.67298189
Minimum-10.616883
Maximum7.4131765
Zeros0
Zeros (%)0.0%
Negative610
Negative (%)0.8%
Memory size571.4 KiB
2025-12-02T18:32:12.989645image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum-10.616883
5-th percentile-4.0493744
Q1-2.0458801
median-0.67948507
Q30.32712504
95-th percentile3.4283661
Maximum7.4131765
Range18.03006
Interquartile range (IQR)2.3730052

Descriptive statistics

Standard deviation2.4078335
Coefficient of variation (CV)-3.5778578
Kurtosis1.7336624
Mean-0.67298189
Median Absolute Deviation (MAD)1.281367
Skewness-0.13545401
Sum-597.60791
Variance5.7976621
MonotonicityNot monotonic
2025-12-02T18:32:13.037167image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0382934570325
 
< 0.1%
-1.40537007624
 
< 0.1%
-0.609212239624
 
< 0.1%
-2.04588012723
 
< 0.1%
-0.792866007522
 
< 0.1%
-3.2298024518
 
< 0.1%
-4.0493743918
 
< 0.1%
-2.3175760918
 
< 0.1%
-0.679485066714
 
< 0.1%
-2.6621927913
 
< 0.1%
Other values (286)689
 
0.9%
(Missing)72237
98.8%
ValueCountFrequency (%)
-10.616883345
< 0.1%
-7.183900966
< 0.1%
-6.7920491544
< 0.1%
-6.0509206141
 
< 0.1%
-6.03969931
 
< 0.1%
-6.0005289711
 
< 0.1%
-5.9501363122
 
< 0.1%
-5.8240417482
 
< 0.1%
-5.5257680262
 
< 0.1%
-5.4721089683
< 0.1%
ValueCountFrequency (%)
7.4131764732
 
< 0.1%
5.9415568033
< 0.1%
5.655850221
 
< 0.1%
5.3384816492
 
< 0.1%
5.1626068125
< 0.1%
4.9759409592
 
< 0.1%
4.862377932
 
< 0.1%
4.6781606042
 
< 0.1%
4.3524698896
< 0.1%
4.1323048911
 
< 0.1%

heat_wave_day
Categorical

Imbalance  Missing 

Distinct2
Distinct (%)0.2%
Missing72237
Missing (%)98.8%
Memory size571.4 KiB
0.0
867 
1.0
 
21

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters2664
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0867
 
1.2%
1.021
 
< 0.1%
(Missing)72237
98.8%

Length

2025-12-02T18:32:13.083399image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-12-02T18:32:13.118082image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0867
97.6%
1.021
 
2.4%

Most occurring characters

ValueCountFrequency (%)
01755
65.9%
.888
33.3%
121
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number1776
66.7%
Other Punctuation888
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
01755
98.8%
121
 
1.2%
Other Punctuation
ValueCountFrequency (%)
.888
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common2664
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
01755
65.9%
.888
33.3%
121
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII2664
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
01755
65.9%
.888
33.3%
121
 
0.8%

heat_stress_category
Categorical

Imbalance  Missing 

Distinct5
Distinct (%)0.6%
Missing72237
Missing (%)98.8%
Memory size571.4 KiB
Comfortable
668 
Warm
150 
Cold
 
49
Hot
 
19
Extreme Heat
 
2

Length

Max length12
Median length11
Mean length9.2623874
Min length3

Characters and Unicode

Total characters8225
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCold
2nd rowComfortable
3rd rowWarm
4th rowWarm
5th rowWarm

Common Values

ValueCountFrequency (%)
Comfortable668
 
0.9%
Warm150
 
0.2%
Cold49
 
0.1%
Hot19
 
< 0.1%
Extreme Heat2
 
< 0.1%
(Missing)72237
98.8%

Length

2025-12-02T18:32:13.154465image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-12-02T18:32:13.192840image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
comfortable668
75.1%
warm150
 
16.9%
cold49
 
5.5%
hot19
 
2.1%
extreme2
 
0.2%
heat2
 
0.2%

Most occurring characters

ValueCountFrequency (%)
o1404
17.1%
m820
10.0%
r820
10.0%
a820
10.0%
C717
8.7%
l717
8.7%
t691
8.4%
e674
8.2%
f668
8.1%
b668
8.1%
Other values (6)226
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7333
89.2%
Uppercase Letter890
 
10.8%
Space Separator2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o1404
19.1%
m820
11.2%
r820
11.2%
a820
11.2%
l717
9.8%
t691
9.4%
e674
9.2%
f668
9.1%
b668
9.1%
d49
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
C717
80.6%
W150
 
16.9%
H21
 
2.4%
E2
 
0.2%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin8223
> 99.9%
Common2
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
o1404
17.1%
m820
10.0%
r820
10.0%
a820
10.0%
C717
8.7%
l717
8.7%
t691
8.4%
e674
8.2%
f668
8.1%
b668
8.1%
Other values (5)224
 
2.7%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII8225
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o1404
17.1%
m820
10.0%
r820
10.0%
a820
10.0%
C717
8.7%
l717
8.7%
t691
8.4%
e674
8.2%
f668
8.1%
b668
8.1%
Other values (6)226
 
2.7%

fasting_insulin
Real number (ℝ)

Missing 

Distinct615
Distinct (%)35.9%
Missing71412
Missing (%)97.7%
Infinite0
Infinite (%)0.0%
Mean10.371967
Minimum1.2
Maximum160
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:13.235656image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1.2
5-th percentile1.99
Q14.52
median8.3
Q313.3
95-th percentile25.64
Maximum160
Range158.8
Interquartile range (IQR)8.78

Descriptive statistics

Standard deviation9.620464
Coefficient of variation (CV)0.92754477
Kurtosis70.654931
Mean10.371967
Median Absolute Deviation (MAD)4.1
Skewness5.8228406
Sum17767.18
Variance92.553328
MonotonicityNot monotonic
2025-12-02T18:32:13.283836image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.99109
 
0.1%
1.932
 
< 0.1%
4.616
 
< 0.1%
4.713
 
< 0.1%
9.713
 
< 0.1%
10.313
 
< 0.1%
12.313
 
< 0.1%
10.712
 
< 0.1%
4.212
 
< 0.1%
3.611
 
< 0.1%
Other values (605)1469
 
2.0%
(Missing)71412
97.7%
ValueCountFrequency (%)
1.21
 
< 0.1%
1.31
 
< 0.1%
1.71
 
< 0.1%
1.82
 
< 0.1%
1.932
 
< 0.1%
1.99109
0.1%
23
 
< 0.1%
2.013
 
< 0.1%
2.021
 
< 0.1%
2.061
 
< 0.1%
ValueCountFrequency (%)
1601
< 0.1%
1561
< 0.1%
87.91
< 0.1%
77.71
< 0.1%
74.71
< 0.1%
621
< 0.1%
58.91
< 0.1%
58.11
< 0.1%
541
< 0.1%
501
< 0.1%

hba1c
Real number (ℝ)

Missing 

Distinct77
Distinct (%)7.8%
Missing72140
Missing (%)98.7%
Infinite0
Infinite (%)0.0%
Mean6.057868
Minimum3.9
Maximum20.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:13.331697image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum3.9
5-th percentile4.8
Q15.4
median5.8
Q36.3
95-th percentile8.3
Maximum20.5
Range16.6
Interquartile range (IQR)0.9

Descriptive statistics

Standard deviation1.361365
Coefficient of variation (CV)0.22472674
Kurtosis22.288068
Mean6.057868
Median Absolute Deviation (MAD)0.5
Skewness3.7109478
Sum5967
Variance1.8533146
MonotonicityNot monotonic
2025-12-02T18:32:13.464776image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5.465
 
0.1%
5.862
 
0.1%
5.361
 
0.1%
5.760
 
0.1%
5.556
 
0.1%
650
 
0.1%
5.650
 
0.1%
6.243
 
0.1%
6.142
 
0.1%
6.442
 
0.1%
Other values (67)454
 
0.6%
(Missing)72140
98.7%
ValueCountFrequency (%)
3.91
 
< 0.1%
42
 
< 0.1%
4.12
 
< 0.1%
4.22
 
< 0.1%
4.36
< 0.1%
4.43
 
< 0.1%
4.53
 
< 0.1%
4.610
< 0.1%
4.710
< 0.1%
4.814
< 0.1%
ValueCountFrequency (%)
20.51
< 0.1%
14.81
< 0.1%
141
< 0.1%
13.81
< 0.1%
13.62
< 0.1%
13.31
< 0.1%
12.81
< 0.1%
12.61
< 0.1%
12.51
< 0.1%
12.31
< 0.1%

hs_crp
Real number (ℝ)

Missing 

Distinct303
Distinct (%)31.7%
Missing72170
Missing (%)98.7%
Infinite0
Infinite (%)0.0%
Mean7.1122513
Minimum0.3
Maximum275.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:13.510692image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.3
5-th percentile0.4
Q11.55
median3.6
Q38.4
95-th percentile23.3
Maximum275.3
Range275
Interquartile range (IQR)6.85

Descriptive statistics

Standard deviation13.263993
Coefficient of variation (CV)1.86495
Kurtosis186.14507
Mean7.1122513
Median Absolute Deviation (MAD)2.5
Skewness10.738867
Sum6792.2
Variance175.93352
MonotonicityNot monotonic
2025-12-02T18:32:13.554094image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.342
 
0.1%
0.617
 
< 0.1%
1.116
 
< 0.1%
0.816
 
< 0.1%
1.316
 
< 0.1%
1.216
 
< 0.1%
1.513
 
< 0.1%
2.712
 
< 0.1%
0.912
 
< 0.1%
1.812
 
< 0.1%
Other values (293)783
 
1.1%
(Missing)72170
98.7%
ValueCountFrequency (%)
0.342
0.1%
0.353
 
< 0.1%
0.48
 
< 0.1%
0.454
 
< 0.1%
0.511
 
< 0.1%
0.553
 
< 0.1%
0.617
< 0.1%
0.654
 
< 0.1%
0.710
 
< 0.1%
0.753
 
< 0.1%
ValueCountFrequency (%)
275.31
< 0.1%
119.51
< 0.1%
104.61
< 0.1%
96.551
< 0.1%
661
< 0.1%
62.31
< 0.1%
57.41
< 0.1%
54.71
< 0.1%
52.751
< 0.1%
49.31
< 0.1%

who_glycemic_status
Categorical

Missing 

Distinct4
Distinct (%)0.4%
Missing72144
Missing (%)98.7%
Memory size571.4 KiB
NGT
721 
T2D
120 
IGT
112 
IFG
 
28

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters2943
Distinct characters7
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowIGT
2nd rowIFG
3rd rowNGT
4th rowNGT
5th rowNGT

Common Values

ValueCountFrequency (%)
NGT721
 
1.0%
T2D120
 
0.2%
IGT112
 
0.2%
IFG28
 
< 0.1%
(Missing)72144
98.7%

Length

2025-12-02T18:32:13.597352image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-12-02T18:32:13.632408image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
ngt721
73.5%
t2d120
 
12.2%
igt112
 
11.4%
ifg28
 
2.9%

Most occurring characters

ValueCountFrequency (%)
T953
32.4%
G861
29.3%
N721
24.5%
I140
 
4.8%
2120
 
4.1%
D120
 
4.1%
F28
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter2823
95.9%
Decimal Number120
 
4.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
T953
33.8%
G861
30.5%
N721
25.5%
I140
 
5.0%
D120
 
4.3%
F28
 
1.0%
Decimal Number
ValueCountFrequency (%)
2120
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2823
95.9%
Common120
 
4.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
T953
33.8%
G861
30.5%
N721
25.5%
I140
 
5.0%
D120
 
4.3%
F28
 
1.0%
Common
ValueCountFrequency (%)
2120
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2943
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
T953
32.4%
G861
29.3%
N721
24.5%
I140
 
4.8%
2120
 
4.1%
D120
 
4.1%
F28
 
1.0%

hip_circumference
Real number (ℝ)

Missing 

Distinct207
Distinct (%)13.2%
Missing71558
Missing (%)97.9%
Infinite0
Infinite (%)0.0%
Mean394.28448
Minimum0.1
Maximum9850
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:13.673610image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile0.87
Q11.02
median1.18
Q3990
95-th percentile1230
Maximum9850
Range9849.9
Interquartile range (IQR)988.98

Descriptive statistics

Standard deviation590.56717
Coefficient of variation (CV)1.49782
Kurtosis45.758259
Mean394.28448
Median Absolute Deviation (MAD)0.24
Skewness3.6390363
Sum617843.78
Variance348769.59
MonotonicityNot monotonic
2025-12-02T18:32:13.721701image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.1330
 
< 0.1%
1.0429
 
< 0.1%
1.0828
 
< 0.1%
1.1227
 
< 0.1%
1.1527
 
< 0.1%
1.0126
 
< 0.1%
1.0526
 
< 0.1%
1.0326
 
< 0.1%
0.9925
 
< 0.1%
0.9425
 
< 0.1%
Other values (197)1298
 
1.8%
(Missing)71558
97.9%
ValueCountFrequency (%)
0.11
 
< 0.1%
0.441
 
< 0.1%
0.671
 
< 0.1%
0.751
 
< 0.1%
0.782
 
< 0.1%
0.796
< 0.1%
0.82
 
< 0.1%
0.812
 
< 0.1%
0.8210
< 0.1%
0.834
 
< 0.1%
ValueCountFrequency (%)
98501
< 0.1%
61251
< 0.1%
19701
< 0.1%
16601
< 0.1%
16201
< 0.1%
16001
< 0.1%
15801
< 0.1%
15501
< 0.1%
15101
< 0.1%
14951
< 0.1%

waist_hip_ratio
Real number (ℝ)

Missing  Skewed 

Distinct1012
Distinct (%)64.6%
Missing71558
Missing (%)97.9%
Infinite0
Infinite (%)0.0%
Mean0.87730209
Minimum0.0047346939
Maximum8.6320755
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:13.768155image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.0047346939
5-th percentile0.72727273
Q10.80220446
median0.86440678
Q30.93159537
95-th percentile1.0245902
Maximum8.6320755
Range8.6273408
Interquartile range (IQR)0.12939091

Descriptive statistics

Standard deviation0.29619376
Coefficient of variation (CV)0.3376189
Kurtosis594.70343
Mean0.87730209
Median Absolute Deviation (MAD)0.06440678
Skewness22.782214
Sum1374.7324
Variance0.087730745
MonotonicityNot monotonic
2025-12-02T18:32:13.813900image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
121
 
< 0.1%
0.8220
 
< 0.1%
0.7819
 
< 0.1%
0.7516
 
< 0.1%
0.815
 
< 0.1%
0.8315
 
< 0.1%
0.8414
 
< 0.1%
0.8114
 
< 0.1%
0.7714
 
< 0.1%
0.7914
 
< 0.1%
Other values (1002)1405
 
1.9%
(Missing)71558
97.9%
ValueCountFrequency (%)
0.0047346938781
< 0.1%
0.0811
< 0.1%
0.083720930231
< 0.1%
0.086294416241
< 0.1%
0.40101522841
< 0.1%
0.5783132531
< 0.1%
0.621
< 0.1%
0.62142857141
< 0.1%
0.63829787231
< 0.1%
0.64485981311
< 0.1%
ValueCountFrequency (%)
8.6320754721
< 0.1%
8.61
< 0.1%
1.8863636361
< 0.1%
1.3592233011
< 0.1%
1.3283582091
< 0.1%
1.2599565491
< 0.1%
1.241
< 0.1%
1.2148760331
< 0.1%
1.1844660191
< 0.1%
1.1724137931
< 0.1%

total_fat_mass
Real number (ℝ)

Missing 

Distinct1642
Distinct (%)95.0%
Missing71397
Missing (%)97.6%
Infinite0
Infinite (%)0.0%
Mean11425.884
Minimum5.55
Maximum67095.009
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:13.857305image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum5.55
5-th percentile10.9705
Q125.475
median46.69
Q322562.392
95-th percentile40933.313
Maximum67095.009
Range67089.459
Interquartile range (IQR)22536.917

Descriptive statistics

Standard deviation14657.775
Coefficient of variation (CV)1.282857
Kurtosis0.021745505
Mean11425.884
Median Absolute Deviation (MAD)35.48
Skewness1.0106201
Sum19743927
Variance2.1485038 × 108
MonotonicityNot monotonic
2025-12-02T18:32:13.906017image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
32.593
 
< 0.1%
36.213
 
< 0.1%
26.933
 
< 0.1%
41.523
 
< 0.1%
19.262
 
< 0.1%
29.662
 
< 0.1%
25.342
 
< 0.1%
34.32
 
< 0.1%
59.62
 
< 0.1%
21.692
 
< 0.1%
Other values (1632)1704
 
2.3%
(Missing)71397
97.6%
ValueCountFrequency (%)
5.551
< 0.1%
6.171
< 0.1%
6.381
< 0.1%
6.521
< 0.1%
6.661
< 0.1%
6.751
< 0.1%
6.931
< 0.1%
7.071
< 0.1%
7.141
< 0.1%
7.261
< 0.1%
ValueCountFrequency (%)
67095.00941
< 0.1%
64562.799461
< 0.1%
63752.163071
< 0.1%
63324.522631
< 0.1%
62653.006681
< 0.1%
59187.927771
< 0.1%
56883.037561
< 0.1%
56013.987921
< 0.1%
55383.269081
< 0.1%
53716.724311
< 0.1%

total_lean_mass
Real number (ℝ)

Missing 

Distinct1613
Distinct (%)93.3%
Missing71397
Missing (%)97.6%
Infinite0
Infinite (%)0.0%
Mean17265.844
Minimum25.3
Maximum58472.474
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:13.953508image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum25.3
5-th percentile38.269
Q148.035
median63.9
Q337408.406
95-th percentile45443.681
Maximum58472.474
Range58447.174
Interquartile range (IQR)37360.371

Descriptive statistics

Standard deviation19498.627
Coefficient of variation (CV)1.1293179
Kurtosis-1.7257821
Mean17265.844
Median Absolute Deviation (MAD)25.505
Skewness0.32946218
Sum29835379
Variance3.8019646 × 108
MonotonicityNot monotonic
2025-12-02T18:32:13.999138image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
46.833
 
< 0.1%
51.533
 
< 0.1%
48.533
 
< 0.1%
44.332
 
< 0.1%
44.52
 
< 0.1%
44.312
 
< 0.1%
44.272
 
< 0.1%
60.532
 
< 0.1%
59.982
 
< 0.1%
40.412
 
< 0.1%
Other values (1603)1705
 
2.3%
(Missing)71397
97.6%
ValueCountFrequency (%)
25.31
< 0.1%
27.671
< 0.1%
28.861
< 0.1%
29.381
< 0.1%
29.511
< 0.1%
29.61
< 0.1%
29.821
< 0.1%
30.261
< 0.1%
30.781
< 0.1%
30.911
< 0.1%
ValueCountFrequency (%)
58472.473581
< 0.1%
58226.271151
< 0.1%
57900.010431
< 0.1%
57050.575581
< 0.1%
56767.804621
< 0.1%
56297.735531
< 0.1%
56265.629231
< 0.1%
55731.688911
< 0.1%
55201.063141
< 0.1%
54073.469111
< 0.1%

body_fat_percent
Real number (ℝ)

Missing 

Distinct1605
Distinct (%)92.9%
Missing71397
Missing (%)97.6%
Infinite0
Infinite (%)0.0%
Mean36.233223
Minimum13.331138
Maximum58.754357
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:14.046230image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum13.331138
5-th percentile18.528863
Q128.425
median37.674659
Q344.2225
95-th percentile50.053404
Maximum58.754357
Range45.423219
Interquartile range (IQR)15.7975

Descriptive statistics

Standard deviation9.7743928
Coefficient of variation (CV)0.26976327
Kurtosis-0.78912739
Mean36.233223
Median Absolute Deviation (MAD)7.5603413
Skewness-0.322624
Sum62611.01
Variance95.538754
MonotonicityNot monotonic
2025-12-02T18:32:14.093685image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
49.443
 
< 0.1%
27.773
 
< 0.1%
37.273
 
< 0.1%
22.883
 
< 0.1%
44.523
 
< 0.1%
39.853
 
< 0.1%
30.013
 
< 0.1%
47.23
 
< 0.1%
44.223
 
< 0.1%
45.192
 
< 0.1%
Other values (1595)1699
 
2.3%
(Missing)71397
97.6%
ValueCountFrequency (%)
13.331137591
< 0.1%
13.371
< 0.1%
13.811
< 0.1%
13.911
< 0.1%
13.961
< 0.1%
13.971
< 0.1%
13.981
< 0.1%
14.142
< 0.1%
14.222
< 0.1%
14.231
< 0.1%
ValueCountFrequency (%)
58.754357091
< 0.1%
58.573369141
< 0.1%
57.633607371
< 0.1%
57.165310181
< 0.1%
56.903818521
< 0.1%
56.842880451
< 0.1%
56.057801261
< 0.1%
55.721
< 0.1%
55.372824691
< 0.1%
55.2160231
< 0.1%

android_fat_percent
Real number (ℝ)

Missing 

Distinct491
Distinct (%)51.5%
Missing72171
Missing (%)98.7%
Infinite0
Infinite (%)0.0%
Mean7.9697945
Minimum3.11
Maximum13.87
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:14.140300image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum3.11
5-th percentile5.59
Q16.84
median7.865
Q39.0025
95-th percentile10.68
Maximum13.87
Range10.76
Interquartile range (IQR)2.1625

Descriptive statistics

Standard deviation1.59414
Coefficient of variation (CV)0.20002272
Kurtosis0.06489699
Mean7.9697945
Median Absolute Deviation (MAD)1.065
Skewness0.20798776
Sum7603.184
Variance2.5412823
MonotonicityNot monotonic
2025-12-02T18:32:14.187563image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.597
 
< 0.1%
7.016
 
< 0.1%
7.466
 
< 0.1%
7.346
 
< 0.1%
9.16
 
< 0.1%
6.185
 
< 0.1%
8.615
 
< 0.1%
8.535
 
< 0.1%
7.45
 
< 0.1%
6.85
 
< 0.1%
Other values (481)898
 
1.2%
(Missing)72171
98.7%
ValueCountFrequency (%)
3.111
< 0.1%
3.721
< 0.1%
3.921
< 0.1%
4.011
< 0.1%
4.071
< 0.1%
4.121
< 0.1%
4.211
< 0.1%
4.261
< 0.1%
4.271
< 0.1%
4.381
< 0.1%
ValueCountFrequency (%)
13.871
< 0.1%
12.731
< 0.1%
12.631
< 0.1%
12.611
< 0.1%
12.531
< 0.1%
12.211
< 0.1%
12.21
< 0.1%
12.161
< 0.1%
12.071
< 0.1%
12.011
< 0.1%

fat_mass_index
Real number (ℝ)

Missing 

Distinct748
Distinct (%)78.6%
Missing72173
Missing (%)98.7%
Infinite0
Infinite (%)0.0%
Mean10.342966
Minimum1.76
Maximum28.408739
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:14.233360image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1.76
5-th percentile2.7355
Q15.875
median9.605
Q314.2825
95-th percentile19.9605
Maximum28.408739
Range26.648739
Interquartile range (IQR)8.4075

Descriptive statistics

Standard deviation5.3870834
Coefficient of variation (CV)0.52084512
Kurtosis-0.50343913
Mean10.342966
Median Absolute Deviation (MAD)4.21
Skewness0.46098568
Sum9846.5035
Variance29.020667
MonotonicityNot monotonic
2025-12-02T18:32:14.278803image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.044
 
< 0.1%
13.924
 
< 0.1%
6.724
 
< 0.1%
8.624
 
< 0.1%
11.744
 
< 0.1%
7.533
 
< 0.1%
11.243
 
< 0.1%
12.343
 
< 0.1%
9.463
 
< 0.1%
17.483
 
< 0.1%
Other values (738)917
 
1.3%
(Missing)72173
98.7%
ValueCountFrequency (%)
1.761
< 0.1%
1.911
< 0.1%
1.981
< 0.1%
21
< 0.1%
2.061
< 0.1%
2.081
< 0.1%
2.091
< 0.1%
2.11
< 0.1%
2.111
< 0.1%
2.131
< 0.1%
ValueCountFrequency (%)
28.408739471
< 0.1%
27.341
< 0.1%
26.141
< 0.1%
261
< 0.1%
24.91
< 0.1%
24.581
< 0.1%
24.471
< 0.1%
24.41
< 0.1%
24.181
< 0.1%
23.891
< 0.1%

asmi
Real number (ℝ)

Missing 

Distinct353
Distinct (%)37.1%
Missing72173
Missing (%)98.7%
Infinite0
Infinite (%)0.0%
Mean4.9302429
Minimum3.02
Maximum8.69
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:14.320962image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum3.02
5-th percentile3.54
Q14.25
median4.91
Q35.51
95-th percentile6.4382654
Maximum8.69
Range5.67
Interquartile range (IQR)1.26

Descriptive statistics

Standard deviation0.90763709
Coefficient of variation (CV)0.18409581
Kurtosis0.029967658
Mean4.9302429
Median Absolute Deviation (MAD)0.63
Skewness0.3624663
Sum4693.5913
Variance0.82380508
MonotonicityNot monotonic
2025-12-02T18:32:14.366413image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5.5110
 
< 0.1%
5.418
 
< 0.1%
4.818
 
< 0.1%
4.237
 
< 0.1%
4.387
 
< 0.1%
4.437
 
< 0.1%
4.797
 
< 0.1%
6.157
 
< 0.1%
4.077
 
< 0.1%
5.827
 
< 0.1%
Other values (343)877
 
1.2%
(Missing)72173
98.7%
ValueCountFrequency (%)
3.021
 
< 0.1%
3.041
 
< 0.1%
3.051
 
< 0.1%
3.061
 
< 0.1%
3.081
 
< 0.1%
3.111
 
< 0.1%
3.173
< 0.1%
3.192
< 0.1%
3.221
 
< 0.1%
3.241
 
< 0.1%
ValueCountFrequency (%)
8.691
< 0.1%
8.441
< 0.1%
7.971
< 0.1%
7.841
< 0.1%
7.331
< 0.1%
7.311
< 0.1%
7.291
< 0.1%
7.281
< 0.1%
7.231
< 0.1%
7.221
< 0.1%

grip_strength
Real number (ℝ)

Missing 

Distinct210
Distinct (%)13.8%
Missing71603
Missing (%)97.9%
Infinite0
Infinite (%)0.0%
Mean32.310138
Minimum9.33
Maximum80.666667
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:14.411138image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum9.33
5-th percentile20
Q126
median30
Q338.5825
95-th percentile50.653
Maximum80.666667
Range71.336667
Interquartile range (IQR)12.5825

Descriptive statistics

Standard deviation9.5061599
Coefficient of variation (CV)0.29421601
Kurtosis0.29150503
Mean32.310138
Median Absolute Deviation (MAD)6
Skewness0.72255231
Sum49176.03
Variance90.367076
MonotonicityNot monotonic
2025-12-02T18:32:14.459116image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3059
 
0.1%
2847
 
0.1%
2646
 
0.1%
28.6741
 
0.1%
2234
 
< 0.1%
2029
 
< 0.1%
2429
 
< 0.1%
30.6727
 
< 0.1%
3226
 
< 0.1%
29.3326
 
< 0.1%
Other values (200)1158
 
1.6%
(Missing)71603
97.9%
ValueCountFrequency (%)
9.331
 
< 0.1%
111
 
< 0.1%
121
 
< 0.1%
13.332
 
< 0.1%
13.672
 
< 0.1%
141
 
< 0.1%
15.334
< 0.1%
15.671
 
< 0.1%
165
< 0.1%
16.672
 
< 0.1%
ValueCountFrequency (%)
80.666666671
 
< 0.1%
65.671
 
< 0.1%
63.332
< 0.1%
62.331
 
< 0.1%
621
 
< 0.1%
59.331
 
< 0.1%
591
 
< 0.1%
583
< 0.1%
57.672
< 0.1%
57.331
 
< 0.1%

epworth_sleepiness_score
Real number (ℝ)

Missing 

Distinct25
Distinct (%)2.5%
Missing72126
Missing (%)98.6%
Infinite0
Infinite (%)0.0%
Mean5.9379379
Minimum0
Maximum24
Zeros85
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:14.502651image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median5
Q38
95-th percentile15
Maximum24
Range24
Interquartile range (IQR)5

Descriptive statistics

Standard deviation4.6274159
Coefficient of variation (CV)0.77929678
Kurtosis1.3293393
Mean5.9379379
Median Absolute Deviation (MAD)3
Skewness1.0960219
Sum5932
Variance21.412978
MonotonicityNot monotonic
2025-12-02T18:32:14.542680image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
3105
 
0.1%
695
 
0.1%
591
 
0.1%
290
 
0.1%
490
 
0.1%
085
 
0.1%
174
 
0.1%
771
 
0.1%
859
 
0.1%
941
 
0.1%
Other values (15)198
 
0.3%
(Missing)72126
98.6%
ValueCountFrequency (%)
085
0.1%
174
0.1%
290
0.1%
3105
0.1%
490
0.1%
591
0.1%
695
0.1%
771
0.1%
859
0.1%
941
 
0.1%
ValueCountFrequency (%)
245
 
< 0.1%
232
 
< 0.1%
222
 
< 0.1%
213
 
< 0.1%
202
 
< 0.1%
193
 
< 0.1%
183
 
< 0.1%
1710
< 0.1%
1612
< 0.1%
1517
< 0.1%

ses_score
Real number (ℝ)

Missing 

Distinct26
Distinct (%)1.6%
Missing71504
Missing (%)97.8%
Infinite0
Infinite (%)0.0%
Mean6.6039482
Minimum0
Maximum32
Zeros55
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:14.578914image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q14
median7
Q39
95-th percentile12
Maximum32
Range32
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.7904798
Coefficient of variation (CV)0.57397177
Kurtosis3.2668918
Mean6.6039482
Median Absolute Deviation (MAD)3
Skewness0.8307773
Sum10705
Variance14.367737
MonotonicityNot monotonic
2025-12-02T18:32:14.617898image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
8233
 
0.3%
6167
 
0.2%
4162
 
0.2%
2161
 
0.2%
7157
 
0.2%
9126
 
0.2%
10126
 
0.2%
11103
 
0.1%
586
 
0.1%
170
 
0.1%
Other values (16)230
 
0.3%
(Missing)71504
97.8%
ValueCountFrequency (%)
055
 
0.1%
170
 
0.1%
2161
0.2%
370
 
0.1%
4162
0.2%
586
 
0.1%
6167
0.2%
7157
0.2%
8233
0.3%
9126
0.2%
ValueCountFrequency (%)
321
 
< 0.1%
311
 
< 0.1%
272
 
< 0.1%
251
 
< 0.1%
221
 
< 0.1%
202
 
< 0.1%
193
 
< 0.1%
188
< 0.1%
171
 
< 0.1%
167
< 0.1%

asset_index
Real number (ℝ)

Missing 

Distinct13
Distinct (%)1.3%
Missing72113
Missing (%)98.6%
Infinite0
Infinite (%)0.0%
Mean8.7183794
Minimum0
Maximum12
Zeros8
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:14.655480image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5
Q17
median9
Q310.25
95-th percentile12
Maximum12
Range12
Interquartile range (IQR)3.25

Descriptive statistics

Standard deviation2.2623959
Coefficient of variation (CV)0.2594973
Kurtosis1.0702233
Mean8.7183794
Median Absolute Deviation (MAD)2
Skewness-0.90433973
Sum8823
Variance5.1184354
MonotonicityNot monotonic
2025-12-02T18:32:14.781207image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
11185
 
0.3%
9183
 
0.3%
10167
 
0.2%
8132
 
0.2%
7126
 
0.2%
1268
 
0.1%
660
 
0.1%
546
 
0.1%
424
 
< 0.1%
08
 
< 0.1%
Other values (3)13
 
< 0.1%
(Missing)72113
98.6%
ValueCountFrequency (%)
08
 
< 0.1%
12
 
< 0.1%
24
 
< 0.1%
37
 
< 0.1%
424
 
< 0.1%
546
 
0.1%
660
 
0.1%
7126
0.2%
8132
0.2%
9183
0.3%
ValueCountFrequency (%)
1268
 
0.1%
11185
0.3%
10167
0.2%
9183
0.3%
8132
0.2%
7126
0.2%
660
 
0.1%
546
 
0.1%
424
 
< 0.1%
37
 
< 0.1%

vitamin_d
Real number (ℝ)

Missing 

Distinct226
Distinct (%)52.2%
Missing72692
Missing (%)99.4%
Infinite0
Infinite (%)0.0%
Mean61.607085
Minimum16.5336
Maximum124.251
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size571.4 KiB
2025-12-02T18:32:14.825659image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum16.5336
5-th percentile31.4736
Q149.302
median60.756
Q373.455
95-th percentile92.6778
Maximum124.251
Range107.7174
Interquartile range (IQR)24.153

Descriptive statistics

Standard deviation18.448214
Coefficient of variation (CV)0.29944955
Kurtosis0.25491921
Mean61.607085
Median Absolute Deviation (MAD)12.201
Skewness0.28409966
Sum26675.868
Variance340.33659
MonotonicityNot monotonic
2025-12-02T18:32:14.873069image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
54.0337
 
< 0.1%
43.3267
 
< 0.1%
57.5196
 
< 0.1%
46.3146
 
< 0.1%
56.2745
 
< 0.1%
56.5235
 
< 0.1%
61.2545
 
< 0.1%
43.8245
 
< 0.1%
53.2865
 
< 0.1%
53.0375
 
< 0.1%
Other values (216)377
 
0.5%
(Missing)72692
99.4%
ValueCountFrequency (%)
16.53361
< 0.1%
19.02361
< 0.1%
20.81641
< 0.1%
21.01561
< 0.1%
22.55941
< 0.1%
23.25661
< 0.1%
23.87911
< 0.1%
24.72571
< 0.1%
25.3982
< 0.1%
25.8961
< 0.1%
ValueCountFrequency (%)
124.2511
< 0.1%
120.5161
< 0.1%
115.7852
< 0.1%
114.0421
< 0.1%
112.5481
< 0.1%
104.0821
< 0.1%
101.0941
< 0.1%
100.5961
< 0.1%
100.0981
< 0.1%
99.1021
< 0.1%

Missing values

2025-12-02T18:32:06.958240image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
A simple visualization of nullity by column.

Sample

study_sourcepatient_idvisit_dateyearmonthseasonlatitudelongitudecityage_yearssexracehiv_statushiv_positiveon_artvirally_suppressedcd4_countviral_loadviral_load_undetectablelog10_viral_loadviral_load_wrhi003_categoryhemoglobinhematocritrbc_countwbc_countplatelet_countmcvmchmchcrdwneutrophils_pctlymphocytes_pctmonocytes_pcteosinophils_pctbasophils_pctfasting_glucoselog10_fasting_glucosetotal_cholesterolhdl_cholesterolldl_cholesteroltriglyceridescreatininecreatinine_clearancebunaltastalptotal_bilirubinalbumintotal_proteinsodiumpotassiumcalciumsystolic_bpdiastolic_bpheart_ratetemperaturerespiratory_rateoxygen_saturationheight_mweight_kgbmiwaist_circumferencetemp_mean_ctemp_max_ctemp_min_ctemp_range_ctemp_lag1dtemp_lag3dtemp_lag7dtemp_lag14dtemp_lag21dtemp_lag30dtemp_variability_7dtemp_variability_30dapparent_temptemp_anomalyheat_wave_dayheat_stress_categoryfasting_insulinhba1chs_crpwho_glycemic_statuship_circumferencewaist_hip_ratiototal_fat_masstotal_lean_massbody_fat_percentandroid_fat_percentfat_mass_indexasmigrip_strengthepworth_sleepiness_scoreses_scoreasset_indexvitamin_d
0JHB_ACTG_01511100602005-11-03NaNNaNNaN-26.204127.9394JohannesburgNaNFemaleNaNPositive1.01.0NaN36.015400.00.0NaNNaN10.332.6NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN39.055.0NaN5.0NaNNaN137.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
1JHB_ACTG_01511100602005-11-03NaNNaNNaN-26.204127.9394JohannesburgNaNFemaleNaNPositive1.01.0NaN35.015400.00.0NaNNaN10.332.6NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN39.055.0NaN5.0NaNNaN137.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
2JHB_ACTG_01511100602005-11-11NaNNaNNaN-26.204127.9394JohannesburgNaNFemaleNaNPositive1.01.0NaN36.0405000.00.0NaNNaN10.332.6NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN39.055.0NaN5.0NaNNaN137.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
3JHB_ACTG_01511100602005-11-11NaNNaNNaN-26.204127.9394JohannesburgNaNFemaleNaNPositive1.01.0NaN35.0405000.00.0NaNNaN10.332.6NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN39.055.0NaN5.0NaNNaN137.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
4JHB_ACTG_01511100602005-12-08NaNNaNNaN-26.204127.9394JohannesburgNaNFemaleNaNPositive1.01.0NaNNaN1020.00.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
study_sourcepatient_idvisit_dateyearmonthseasonlatitudelongitudecityage_yearssexracehiv_statushiv_positiveon_artvirally_suppressedcd4_countviral_loadviral_load_undetectablelog10_viral_loadviral_load_wrhi003_categoryhemoglobinhematocritrbc_countwbc_countplatelet_countmcvmchmchcrdwneutrophils_pctlymphocytes_pctmonocytes_pcteosinophils_pctbasophils_pctfasting_glucoselog10_fasting_glucosetotal_cholesterolhdl_cholesterolldl_cholesteroltriglyceridescreatininecreatinine_clearancebunaltastalptotal_bilirubinalbumintotal_proteinsodiumpotassiumcalciumsystolic_bpdiastolic_bpheart_ratetemperaturerespiratory_rateoxygen_saturationheight_mweight_kgbmiwaist_circumferencetemp_mean_ctemp_max_ctemp_min_ctemp_range_ctemp_lag1dtemp_lag3dtemp_lag7dtemp_lag14dtemp_lag21dtemp_lag30dtemp_variability_7dtemp_variability_30dapparent_temptemp_anomalyheat_wave_dayheat_stress_categoryfasting_insulinhba1chs_crpwho_glycemic_statuship_circumferencewaist_hip_ratiototal_fat_masstotal_lean_massbody_fat_percentandroid_fat_percentfat_mass_indexasmigrip_strengthepworth_sleepiness_scoreses_scoreasset_indexvitamin_d
73120JHB_WRHI_003992017-01-05NaNNaNNaN-26.204128.0473Johannesburg38.0FemaleBlackPositive1.01.0NaNNaN0.01.0NaNNaN14.4NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN60.0107.0NaN39.027.0NaNNaNNaNNaNNaNNaNNaN124.081.070.0NaNNaNNaNNaN58.822.131055NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
73121JHB_WRHI_003992017-03-23NaNNaNNaN-26.204128.0473Johannesburg38.0FemaleBlackPositive1.01.0NaNNaN0.01.0NaNNaN14.6NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN4.101.102.95NaN64.0103.0NaN33.025.0NaNNaNNaNNaNNaNNaNNaN121.080.080.0NaNNaNNaNNaN58.822.131055NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
73122JHB_WRHI_003992017-06-15NaNNaNNaN-26.204128.0473Johannesburg38.0FemaleBlackPositive1.01.0NaNNaN0.01.0NaNNaN15.7NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN123.082.072.0NaNNaNNaNNaN58.822.131055NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
73123JHB_WRHI_003992017-09-05NaNNaNNaN-26.204128.0473Johannesburg38.0FemaleBlackPositive1.01.0NaN766.00.01.0NaNNaN15.2NaNNaNNaNNaN91.031.834.913.4NaNNaNNaNNaNNaN4.5NaN4.851.173.36NaN62.0109.0NaN42.029.0NaNNaNNaNNaNNaNNaNNaN117.088.064.0NaNNaNNaNNaN58.822.131055NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
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